DETAILED ACTION
This action is in reply to the Amendments filed on 02/25/2026.
Claim 10 was previously cancelled.
Claims 1-9 and 11-23 are rejected.
Claims 1-9 and 11-23 are currently pending and have been examined.
Response to Amendment
Applicant’s amendment, filed 02/25/2026, has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9, 11-18 and 20-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under Step 1 of the Subject Matter Eligibility Test for Products and Processes, the claims must be directed to one of the four statutory categories (see MPEP 2106.03). All the claims are directed to one of the four statutory categories (YES).
Under Step 2A of the Subject Matter Eligibility Test, it is determined whether the claims are directed to a judicially recognized exception (see MPEP 2106.04). Step 2A is a two-prong inquiry.
Under Prong 1, it is determined whether the claim recites a judicial exception (YES). Taking Claim 1 as representative, the claim recites limitations that fall within the certain methods of organizing human activity groupings of abstract ideas, including:
-a processing unit configured to execute instructions to cause the system to:
-obtain attribute tags associated with items;
-detect an event;
-in response to the event, generate a search navigation graph based on a search navigation template graph, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag, and wherein the search navigation graph includes only nodes of the search navigation template graph representing the attribute tags associated with the items; and
-cause a search navigation bar in a user interface to be displayed[ing] with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph
The above limitations recite the concept of generating a search navigation graph in response to an event, the search navigation graph including nodes that represent attribute tags associated with items. The above limitations fall within the “Certain Methods of Organizing Human Activity” groupings of abstract ideas, enumerated in MPEP 2106.04(a).
The limitations of obtain attribute tags associated with items; detect an event; and in response to the event, generate a search navigation graph based on a search navigation template graph, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag, and wherein the search navigation graph includes only nodes of the search navigation template graph representing the attribute tags associated with the items, are processes that, under their broadest reasonable interpretation, cover a commercial interaction. For example, “obtain,” “detect,” and “generate” in the context of this claim encompass advertising, and marketing or sales activities.
The limitation of cause a search navigation bar in a user interface to be displayed[ing] with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph is a process that, under its broadest reasonable interpretation, cover a commercial interaction. That is, other than reciting causing a search navigation bar in a user interface to be displayed with selectable icons and that the selectable icons are the representation, nothing in the claim element precludes the step from practically being performed by people. For example, but for the “search navigation bar,” “user interface,” and “selectable icons” language, “displayed” ” in the context of this claim encompasses advertising, and marketing or sales activities.
Under Prong 2, it is determined whether the claim recites additional elements that integrate the exception into a practical application of the exception. This judicial exception is not integrated into a practical application (NO).
-a processing unit configured to execute instructions to cause the system to:
-obtain attribute tags associated with items;
-detect an event;
-in response to the event, generate a search navigation graph based on a search navigation template graph, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag, and wherein the search navigation graph includes only nodes of the search navigation template graph representing the attribute tags associated with the items; and
-cause a search navigation bar in a user interface to be displayed with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph
These limitations are not indicative of integration into a practical application because:
The additional elements of claim 1 are recited at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than mere instructions to implement or apply the abstract idea on a generic computing hardware (or, merely use a computer as a tool to perform an abstract idea) as supported by paragraph [40] of Applicant’s specification – “a customer may interact with the platform 100 through a customer device 150 (e.g., computer, laptop computer, mobile computing device, or the like), a POS device 152 (e.g., retail device, kiosk, automated (self-service) checkout system, or the like), and/or any other commerce interface device known in the art.” Specifically, the additional elements of a processing unit configured to execute instructions, causing a search navigation bar in a user interface to be displayed with selectable icons, and the selectable icons are recited at a high-level of generality (i.e. as a generic processor performing the generic computer functions of obtaining data, detecting data, generating data, and displaying data) such that they amount do no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. Further, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (such as computers or computing networks). Employing well-known computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, does not integrate the exception into a practical application.
Additionally, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to i) reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, ii) apply the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, iii) effect a transformation or reduction of a particular article to a different state or thing, or iv) apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, the judicial exception is not integrated into a practical application.
Under Step 2B, it is determined whether the claims recite additional elements that amount to significantly more than the judicial exception. The claims of the present application do not include additional elements that are sufficient to amount to significantly more than the judicial exception (NO).
In the case of claim 1, taken individually or as a whole, the additional elements of claim 1 do not provide an inventive concept. As discussed above under step 2A (prong 2) with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed functions amount to no more than a general link to a technological environment.
Even considered as an ordered combination (as a whole), the additional elements do not add anything significantly more than when considered individually.
Claim 12 is a search navigation method reciting similar functions as claim 1. Examiner notes that claim 12 recites the additional elements of causing a search navigation bar in a user interface to be displayed with selectable icons, and the selectable icons, however, claim 12 does not qualify as eligible subject matter for similar reasons as claim 1 indicated above.
Claim 21 is a computer-readable medium reciting similar functions as claim 1. Examiner notes that claim 21 recites the additional elements of a computer-readable medium, a processor, causing a search navigation bar in a user interface to be displayed with selectable icons, and the selectable icons, however, claim 21 does not qualify as eligible subject matter for similar reasons as claim 1 indicated above.
Therefore, claims 1, 12, and 21 do not provide an inventive concept and do not qualify as eligible subject matter.
Dependent claims 2-9, 11, 13-18, 20 and 22-23, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. § 101 because they do not add “significantly more” to the abstract idea. More specifically, dependent claims 2-9, 11, 13-18, 20 and 22-23 further fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas in that they recite commercial interactions. Dependent claims 11, 13-16 do not recite any farther additional elements, and as such are not indicative of integration into a practical application for at least similar reasons discussed above. Dependent claims 2-9, 17-18, 20 and 22-23 recite the additional elements of the processing unit, causing the search navigation bar on the user interface to be updated, a memory in communication with the processing unit, the memory being configured to store a copy of the search navigation graph, and storing a copy of the search navigation graph, but similar to the analysis under prong two of Step 2A these additional elements are used as a tool to perform the abstract idea. As such, under prong two of Step 2A, claims 2-11, 13-18, 20 and 22-23 are not indicative of integration into a practical application for at least similar reasons as discussed above. Thus, dependent claims 2-11, 13-18, 20 and 22-23 are “directed to” an abstract idea. Next, under Step 2B, similar to the analysis of claims 1, 12, and 21, dependent claims 2-11, 13-18, 20 and 22-23 when analyzed individually and as an ordered combination, merely further define the commonplace business method (i.e. generating a search navigation graph in response to a buyer event, the search navigation graph including nodes that represent attribute tags associated with the available inventory of a store) being applied on a general-purpose computer and, therefore, do not amount to significantly more than the abstract idea itself. Accordingly, the Examiner concludes that there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself. The analysis above applies to all statutory categories of invention.
Eligible Subject Matter
Claim 19 is eligible over 101 as the abstract idea is integrated into a practical application under Prong Two of Step 2A. Specifically, the recitations of regenerating the search navigation graph in response to a depletion of available inventory causing the displayed selectable icon corresponding to the particular attribute tag to become grayed-out in the search navigation bar applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 9, 11-14, 18, and 20-23 are rejected under 35 U.S.C. 103 as being unpatentable over Gregov et al. (US 8,560,398 B1), hereinafter Gregov, in view of Pillarisetty et al. (US 2022/0035876 A1), hereinafter Pillarisetty.
Regarding claim 1, Gregov discloses search navigation system comprising:
-a processing unit configured to execute instructions (Gregov, see at least: “The computers, servers, and the like described herein have the necessary electronics, software, memory, storage, databases, firmware, logic/state machines, microprocessors, communication links, displays or other visual or audio user interfaces, printing devices, and any other input/output interfaces to perform the functions described herein and/or achieve the results described herein” Col. 4 Ln. 15-21) to cause the system to:
-obtain attribute tags associated with items (Gregov, see at least: “The grouping of items from the list 300 may be accomplished using browse nodes associated with a browse tree, such as that discussed hereinbefore with FIGS. 5-7, and assigning a respective one of the tags 106 (FIG. 2) for each of the selected browse nodes [i.e. obtain attribute tags]” Col. 11 Ln. 27-31 and “a process 500 for generating the tag cloud 106 (FIG. 2) may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations [i.e. obtain attribute tags]” Col. 11 Ln. 46-49 “it is known in the art of computer databases and computer-based websites to use "browse trees" to help categorize and/or identify items … As the name suggests, the "browse" tree 400 permits users (or the merchant) to "browse" through various items, which are logically arranged in the form of a hierarchical tree arrangement of browse nodes 402-418, having a plurality of different levels 420. Each of the browse nodes 402-418 may be associated with a category of items in a hierarchical manner [i.e. obtain attribute tags associated with items]. Thus, the browse tree 400 may be viewed as a collection of categories, each category corresponding to one of the browse nodes 402-418 of the tree 400 and each of the browse nodes 402-418 being associated with one or more items” Col. 9 Ln. 31-47 and “Referring to FIG. 7, similarly, in a "DVDs" tree 700, having a root node 702, there may be a node 704 called "Sci-Fi/Fantasy" [i.e. obtain attribute tags]” Col. 10 Ln. 44-45);
-detect an event (Gregov, see at least: “The display sections 104,108 may be part of the larger window 102 or they may be separate detached or detachable windows within the main website screen 100. The window 102 may be displayed upon access of the web site or upon login by the customer 10 to the merchant's website 22 [i.e. detect an event]” Col. 5 Ln. 36-40);
-in response to the event, generate a search navigation graph based on a search navigation template graph, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag (Gregov, see at least: “The display sections 104,108 may be part of the larger window 102 or they may be separate detached or detachable windows within the main website screen 100. The window 102 may be displayed upon access of the web site or upon login by the customer 10 to the merchant's website 22 [i.e. in response to the event]” Col. 5 Ln. 36-40 and “a process 500 for generating the tag cloud 106 (FIG. 2) may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations [i.e. generate a search navigation graph based on a search navigation template graph], as discussed hereinbefore with respect to FIG. 4. Next, a block 504 identifies the lowest level nodes having at least a threshold number of items (here, three items) and creates a node table 350 (FIG. 4). The node table 350 (FIG. 4) has a Node Name column 352 that lists the names of the lowest level nodes having at least three items. If a given node has less than three items, that node is not used and the next higher level node is used instead as the selected node (provided it meets the other criteria discussed herein). As discussed hereinbefore with FIGS. 5-7, the next higher level node includes all the items of the lower nodes. Also, if there is a browse node name that is not sufficiently descriptive, is uninformative, or is otherwise not appropriate to be included in the recommendations for the customer 10 as determined by the merchant 20, that node is also not used and the next higher node is used instead as the selected node (provided it meets the other criteria discussed herein) [i.e. generate a search navigation graph]” Col. 11 Ln. 46-66 and “The relevance score provides an indication of how relevant a particular node is likely to be for the customer 10. For example, deep browse nodes, e.g., digital photography (level 3) (FIG. 6) are preferred to top level nodes, e.g., "Art & Photography" (level 1)(FIG. 6), because they tend to provide more specific information to the customer 10 in the tag cloud 106 about recommended items [i.e. the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag]” Col. 12 Ln. 32-38 and Fig. 8), and
-wherein the search navigation graph includes nodes of the search navigation template graph representing the attribute tags associated with the items (Gregov, see at least: “a "root" node 402 of the tree 400 may represent all or a subset of items in a given category of items on the merchant 20 website 22, such as "Books," "DVDs", "Electronics," "Tools and Automotive," etc. Each root browse node 402 may have different child browse nodes 404-410 representing sub-categories under the parent or root node 402. Similarly, each of the child nodes 404-410 may have different lower level child nodes, e.g., for node 408, there may be three child nodes 412-416. Also, under each of the nodes 412-416 there may be one or more lower level child nodes, such as the node 418. At the bottom of the tree 400 is a "leaf" node 418 that has associated with it one or more actual items or products (i.e., "leaves"), which are available for purchase [i.e. wherein the search navigation graph includes nodes of the search navigation template graph representing the attribute tags associated with the items] and are all related to the leaf node 418” Col. 9 Ln. 55-67 & Col. 10 Ln. 1); and
-cause a search navigation bar in a user interface to be displayed with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106 [i.e. cause a search navigation bar in a user interface to be displayed with selectable icons], e.g., tag 120 "Action and Adventure", a box 121 appears around the tag 120 and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively” Col. 6 Ln. 57-63 and “when the merchant's web site displays the tag cloud 104, each of the categories or tags 106 is displayed having a predetermined quantity identifier 111, e.g., font size, indicative of the number (or quantity) of recommended items associated with that tag. The larger the tag font size, the more recommended items there are associated with that tag. Accordingly, for the example shown in FIG. 2, the tags 120 (Action & Adventure), 122 (Contemporary), 124 (Picture Books), and 126 (Humorous), have more recommendations than the rest of the tags 106 because they have the largest font sizes in the tag cloud 104 [i.e. the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph]” Col. 5 Ln. 59-67 & Col. 6 Ln. 1-2 and “the tags may be images, icons, [i.e. selectable icons] video or other visual representations of categories. For example, a sporting goods category could be represented by an icon depicting a tennis racket and a romance category could be represented by a heart. In such embodiments, the visual effect may include using contrasting sizes or colors of the visual representation, among other possibilities” Col. 6 Ln. 48-55 and Fig. 2 indicates that the tag cloud includes selectable icons of the attribute tags).
Gregov does not explicitly disclose the search navigation graph includes only nodes of the search navigation template graph representing attribute tags associated with the items.
Pillarisetty, however, teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the search navigation graph including only nodes of the search navigation template graph representing attribute tags associated with the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the search navigation graph includes only nodes of the search navigation template graph representing attribute tags associated with the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system. Further, it should be noted that FIG. 4 is illustrated as one example of a hierarchical data structure that may be stored by the inventory management system 100, and that other hierarchical data structures may be adapted with any appropriate hierarchy with any appropriate number of nodes and connectors as necessary” [0036] and Fig. 4). This known technique is applicable to the system of Gregov as they share characteristics and capabilities, namely, they are directed to a data structure storing a hierarchical data structure.
It would have been recognized that applying the known technique of the search navigation graph including only nodes of the search navigation template graph representing attribute tags associated with the items, as taught by Pillarisetty, to the teachings of Gregov would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such references into similar systems. Further, including the modification of the search navigation graph including only nodes of the search navigation template graph representing attribute tags associated with the items, as taught by Pillarisetty, into the system of Gregov would have been recognized by those of ordinary skill in the art as resulting in an improved system that would provide an improved search function for finding information (Pillarisetty, [0042]).
Regarding claim 2, Gregov in view of Pillarisetty teaches the system of claim 1. Gregov further discloses:
-wherein the processing unit is further configured to generate the search navigation graph by: pruning the search navigation template graph by removing a subgraph from the search navigation template graph (Gregov, see at least: “if there is a browse node name that is not sufficiently descriptive, is uninformative, or is otherwise not appropriate to be included in the recommendations for the customer 10 as determined by the merchant 20, that node is also not used and the next higher node is used instead as the selected node (provided it meets the other criteria discussed herein) [i.e. wherein the processing unit is further configured to generate the search navigation graph by: pruning the search navigation template graph by removing a subgraph from the search navigation template graph]. For example, node names such as "16:10", "10.times. to 19.times.", "2 to 2.9 MP", "$100-199", may be nodes that are considered uninformative. These inappropriate nodes may be culled from the list manually and/or, where possible, using automated methods. An automated method may include, for example, removing any categories with no words and/or no words found in a customized or generic dictionary” Col. 11 Ln. 60-67 & Col. 12 Ln. 1-6).
Gregov does not explicitly disclose the removed subgraph containing nodes representing attribute tags that are not associated with the items.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the removed subgraph containing nodes representing attribute tags that are not associated with the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the removed subgraph contains nodes representing attribute tags that are not associated with the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system. Further, it should be noted that FIG. 4 is illustrated as one example of a hierarchical data structure that may be stored by the inventory management system 100, and that other hierarchical data structures may be adapted with any appropriate hierarchy with any appropriate number of nodes and connectors as necessary” [0036] and Fig. 4 indicates that the product node is a subgraph from the offer node). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 1.
Regarding claim 3, Gregov in view of Pillarisetty teaches the system of claim 2. Gregov further discloses:
-wherein the processing unit is further configured to generate the search navigation graph by: shrinking the search navigation template graph by identifying a hierarchical level in the search navigation template graph that contains only a single node and removing the identified hierarchical level from the search navigation template graph (Gregov, see at least: “a process 500 for generating the tag cloud 106 (FIG. 2) [i.e. generate the search navigation graph by:] may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations, as discussed hereinbefore with respect to FIG. 4. Next, a block 504 identifies the lowest level nodes having at least a threshold number of items (here, three items) and creates a node table 350 (FIG. 4). The node table 350 (FIG. 4) has a Node Name column 352 that lists the names of the lowest level nodes having at least three items. If a given node has less than three items, that node is not used and the next higher level node is used instead as the selected node (provided it meets the other criteria discussed herein) [i.e. shrinking the search navigation template graph by identifying a hierarchical level in the search navigation template graph that contains only a single node and removing the identified hierarchical level from the search navigation template graph]” Col. 11 Ln. 46-58).
Regarding claim 9, Gregov in view of Pillarisetty teaches the system of claim 1. Gregov further discloses:
-wherein the processing unit is further configured to apply a filter to the items, regenerate the search navigation graph to correspond to the filtered items, and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106, e.g., tag 120 "Action and Adventure" [i.e. wherein the processing unit is further configured to apply a filter to the items], a box 121 appears around the tag 120 and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively [i.e. regenerate the search navigation graph to correspond to the filtered items, and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph]” Col. 6 Ln. 57-63 and Fig. 2).
Regarding claim 11, Gregov in view of Pillarisetty teaches the system of claim 1. Gregov further discloses:
-wherein the attribute tags are visual attribute tags associated with visual attributes of the items (Gregov, see at least: “the tags may be images, icons, video or other visual representations of categories. For example, a sporting goods category could be represented by an icon depicting a tennis racket [i.e. wherein the attribute tags are visual attribute tags associated with visual attributes of the items] and a romance category could be represented by a heart” Col. 6 Ln. 48-55).
Regarding claim 12, Gregov discloses a search navigation method comprising:
-obtaining attribute tags associated with items (Gregov, see at least: “The grouping of items from the list 300 may be accomplished using browse nodes associated with a browse tree, such as that discussed hereinbefore with FIGS. 5-7, and assigning a respective one of the tags 106 (FIG. 2) for each of the selected browse nodes [i.e. obtaining attribute tags]” Col. 11 Ln. 27-31 and “a process 500 for generating the tag cloud 106 (FIG. 2) may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations [i.e. obtaining attribute tags]” Col. 11 Ln. 46-49 “it is known in the art of computer databases and computer-based websites to use "browse trees" to help categorize and/or identify items … As the name suggests, the "browse" tree 400 permits users (or the merchant) to "browse" through various items, which are logically arranged in the form of a hierarchical tree arrangement of browse nodes 402-418, having a plurality of different levels 420. Each of the browse nodes 402-418 may be associated with a category of items in a hierarchical manner [i.e. obtaining attribute tags associated with items]. Thus, the browse tree 400 may be viewed as a collection of categories, each category corresponding to one of the browse nodes 402-418 of the tree 400 and each of the browse nodes 402-418 being associated with one or more items” Col. 9 Ln. 31-47 and “Referring to FIG. 7, similarly, in a "DVDs" tree 700, having a root node 702, there may be a node 704 called "Sci-Fi/Fantasy" [i.e. obtaining attribute tags]” Col. 10 Ln. 44-45);
-detecting an event (Gregov, see at least: “The display sections 104,108 may be part of the larger window 102 or they may be separate detached or detachable windows within the main website screen 100. The window 102 may be displayed upon access of the web site or upon login by the customer 10 to the merchant's website 22 [i.e. detecting an event]” Col. 5 Ln. 36-40);
-in response to the event, generating a search navigation graph based on a search navigation template graph and the attribute tags, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag (Gregov, see at least: “The display sections 104,108 may be part of the larger window 102 or they may be separate detached or detachable windows within the main website screen 100. The window 102 may be displayed upon access of the web site or upon login by the customer 10 to the merchant's website 22 [i.e. in response to the event]” Col. 5 Ln. 36-40 and “a process 500 for generating the tag cloud 106 (FIG. 2) may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations [i.e. generating a search navigation graph based on a search navigation template graph and the attribute tags], as discussed hereinbefore with respect to FIG. 4. Next, a block 504 identifies the lowest level nodes having at least a threshold number of items (here, three items) and creates a node table 350 (FIG. 4). The node table 350 (FIG. 4) has a Node Name column 352 that lists the names of the lowest level nodes having at least three items. If a given node has less than three items, that node is not used and the next higher level node is used instead as the selected node (provided it meets the other criteria discussed herein). As discussed hereinbefore with FIGS. 5-7, the next higher level node includes all the items of the lower nodes. Also, if there is a browse node name that is not sufficiently descriptive, is uninformative, or is otherwise not appropriate to be included in the recommendations for the customer 10 as determined by the merchant 20, that node is also not used and the next higher node is used instead as the selected node (provided it meets the other criteria discussed herein) [i.e. generating a search navigation graph]” Col. 11 Ln. 46-66 and “The relevance score provides an indication of how relevant a particular node is likely to be for the customer 10. For example, deep browse nodes, e.g., digital photography (level 3) (FIG. 6) are preferred to top level nodes, e.g., "Art & Photography" (level 1)(FIG. 6), because they tend to provide more specific information to the customer 10 in the tag cloud 106 about recommended items [i.e. the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag]” Col. 12 Ln. 32-38 and Fig. 8), and
-wherein the search navigation graph includes nodes of the search navigation template graph representing the attribute tags associated with the items (Gregov, see at least: “a "root" node 402 of the tree 400 may represent all or a subset of items in a given category of items on the merchant 20 website 22, such as "Books," "DVDs", "Electronics," "Tools and Automotive," etc. Each root browse node 402 may have different child browse nodes 404-410 representing sub-categories under the parent or root node 402. Similarly, each of the child nodes 404-410 may have different lower level child nodes, e.g., for node 408, there may be three child nodes 412-416. Also, under each of the nodes 412-416 there may be one or more lower level child nodes, such as the node 418. At the bottom of the tree 400 is a "leaf" node 418 that has associated with it one or more actual items or products (i.e., "leaves"), which are available for purchase [i.e. wherein the search navigation graph includes nodes of the search navigation template graph representing the attribute tags associated with the items] and are all related to the leaf node 418” Col. 9 Ln. 55-67 & Col. 10 Ln. 1); and
-causing a search navigation bar in a user interface to be displayed with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106 [i.e. causing a search navigation bar in a user interface to be displayed with selectable icons], e.g., tag 120 "Action and Adventure", a box 121 appears around the tag 120 and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively” Col. 6 Ln. 57-63 and “when the merchant's web site displays the tag cloud 104, each of the categories or tags 106 is displayed having a predetermined quantity identifier 111, e.g., font size, indicative of the number (or quantity) of recommended items associated with that tag. The larger the tag font size, the more recommended items there are associated with that tag. Accordingly, for the example shown in FIG. 2, the tags 120 (Action & Adventure), 122 (Contemporary), 124 (Picture Books), and 126 (Humorous), have more recommendations than the rest of the tags 106 because they have the largest font sizes in the tag cloud 104 [i.e. the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph]” Col. 5 Ln. 59-67 & Col. 6 Ln. 1-2 and “the tags may be images, icons, [i.e. selectable icons] video or other visual representations of categories. For example, a sporting goods category could be represented by an icon depicting a tennis racket and a romance category could be represented by a heart. In such embodiments, the visual effect may include using contrasting sizes or colors of the visual representation, among other possibilities” Col. 6 Ln. 48-55 and Fig. 2 indicates that the tag cloud includes selectable icons of the attribute tags).
Gregov does not explicitly disclose the search navigation graph includes only nodes of the search navigation template graph representing the attribute tags associated with the items.
Pillarisetty, however, teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the search navigation graph including only nodes of the search navigation template graph representing attribute tags associated with the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the search navigation graph includes only nodes of the search navigation template graph representing attribute tags associated with the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system. Further, it should be noted that FIG. 4 is illustrated as one example of a hierarchical data structure that may be stored by the inventory management system 100, and that other hierarchical data structures may be adapted with any appropriate hierarchy with any appropriate number of nodes and connectors as necessary” [0036] and Fig. 4). This known technique is applicable to the method of Gregov as they share characteristics and capabilities, namely, they are directed to a data structure storing a hierarchical data structure.
It would have been recognized that applying the known technique of the search navigation graph including only nodes of the search navigation template graph representing attribute tags associated with the items, as taught by Pillarisetty, to the teachings of Gregov would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such references into similar methods. Further, including the modification of the search navigation graph including only nodes of the search navigation template graph representing attribute tags associated with the items, as taught by Pillarisetty, into the method of Gregov would have been recognized by those of ordinary skill in the art as resulting in an improved method that would provide an improved search function for finding information (Pillarisetty, [0042]).
Regarding claim 13, Gregov in view of Pillarisetty teaches the method of claim 12. Gregov further discloses:
-wherein generating the search navigation graph comprises: pruning the search navigation template graph by removing a subgraph from the search navigation template graph (Gregov, see at least: “if there is a browse node name that is not sufficiently descriptive, is uninformative, or is otherwise not appropriate to be included in the recommendations for the customer 10 as determined by the merchant 20, that node is also not used and the next higher node is used instead as the selected node (provided it meets the other criteria discussed herein) [i.e. wherein generating the search navigation graph comprises: pruning the search navigation template graph by removing a subgraph from the search navigation template graph]. For example, node names such as "16:10", "10.times. to 19.times.", "2 to 2.9 MP", "$100-199", may be nodes that are considered uninformative. These inappropriate nodes may be culled from the list manually and/or, where possible, using automated methods. An automated method may include, for example, removing any categories with no words and/or no words found in a customized or generic dictionary” Col. 11 Ln. 60-67 & Col. 12 Ln. 1-6).
Gregov does not explicitly disclose the removed subgraph containing nodes representing attribute tags that are not associated with the items.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the removed subgraph containing nodes representing attribute tags that are not associated with the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the removed subgraph contains nodes representing attribute tags that are not associated with the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system. Further, it should be noted that FIG. 4 is illustrated as one example of a hierarchical data structure that may be stored by the inventory management system 100, and that other hierarchical data structures may be adapted with any appropriate hierarchy with any appropriate number of nodes and connectors as necessary” [0036] and Fig. 4 indicates that the product node is a subgraph from the offer node). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 12.
Regarding claim 14, Gregov in view of Pillarisetty teaches the method of claim 13. Gregov further discloses:
-wherein generating the search navigation graph further comprises: shrinking the search navigation template graph by identifying a hierarchical level in the search navigation template graph that contains only a single node and removing the identified hierarchical level from the search navigation template graph (Gregov, see at least: “a process 500 for generating the tag cloud 106 (FIG. 2) [i.e. generating the search navigation graph further comprises:] may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations, as discussed hereinbefore with respect to FIG. 4. Next, a block 504 identifies the lowest level nodes having at least a threshold number of items (here, three items) and creates a node table 350 (FIG. 4). The node table 350 (FIG. 4) has a Node Name column 352 that lists the names of the lowest level nodes having at least three items. If a given node has less than three items, that node is not used and the next higher level node is used instead as the selected node (provided it meets the other criteria discussed herein) [i.e. shrinking the search navigation template graph by identifying a hierarchical level in the search navigation template graph that contains only a single node and removing the identified hierarchical level from the search navigation template graph]” Col. 11 Ln. 46-58).
Regarding claim 18, Gregov in view of Pillarisetty teaches the method of claim 12. Gregov further discloses:
-storing a copy of the search navigation graph after the search navigation graph is generated (Gregov, see at least: “Thus, the browse tree 400 may be viewed as a collection of categories, each category corresponding to one of the browse nodes 402-418 of the tree 400 and each of the browse nodes 402-418 being associated with one or more items. The merchant server 24 may store the information and relationships associated with one or more browse trees for all items sold by the merchant. Accordingly, the browse tree 400 may be used by the merchant website 22 to display categories or groups of items for the customer 10 to use while shopping or browsing the merchant website 22 as well as used to categorize and/or identify items for various uses [i.e. storing a copy of the search navigation graph after the search navigation graph is generated]” Col. 9 Ln. 44-54 and “The window 102 may be displayed upon access of the web site or upon login by the customer 10 to the merchant's website 22, or at any other time. At the top of the window 102, is a main title header 110, which states, "Recommendations For You"” Col. 5 Ln. 38-42 and “Prior to the Customer 10 selecting one of the tags 106 in the tag cloud 104, the viewer 108 displays a default view of items, e.g., the "All Categories" tag items. In some embodiments, the default view for the viewer 108 may be the display of items associated with a tag having the most items, the items most relevant to the customer 10 [i.e. storing a copy of the search navigation graph after the search navigation graph is generated], or any other criteria” Col. 7 Ln. 5-10).
Regarding claim 20, Gregov in view of Pillarisetty teaches the method of claim 12. Gregov further discloses:
-applying a filter to the items, regenerating the search navigation graph to correspond to the filtered items, and causing the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106, e.g., tag 120 "Action and Adventure" [i.e. applying a filter to the items], a box 121 appears around the tag 120 and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively [i.e. regenerating the search navigation graph to correspond to the filtered items, and causing the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph]” Col. 6 Ln. 57-63 and Fig. 2).
Claim 21 recites limitations directed towards a computer-readable medium storing instructions that, when executed by a processor of a system (Gregov, see at least: “The computers, servers, and the like described herein have the necessary electronics, software, memory, storage, databases, firmware, logic/state machines, microprocessors, communication links, displays or other visual or audio user interfaces, printing devices, and any other input/output interfaces to perform the functions described herein and/or achieve the results described herein” Col. 4 Ln. 15-21). The limitations recited in claim 21 is parallel in nature to those addressed above for claim 12, and are therefore rejected for those same reasons set forth above in claim 12.
Regarding claim 22, Gregov in view of Pillarisetty teaches the system of claim 1. Gregov further discloses:
-regenerate the search navigation graph, wherein regenerating the search navigation graph comprises removing the node representing the particular attribute tag from the search navigation graph (Gregov, see at least: “if there is a browse node name that is not sufficiently descriptive, is uninformative, or is otherwise not appropriate to be included in the recommendations [i.e. regenerate the search navigation graph, wherein regenerating the search navigation graph] for the customer 10 as determined by the merchant 20, that node is also not used [i.e. comprises removing the node representing the particular attribute tag from the search navigation graph] and the next higher node is used instead as the selected node (provided it meets the other criteria discussed herein). For example, node names such as "16:10", "10.times. to 19.times.", "2 to 2.9 MP", "$100-199", may be nodes that are considered uninformative. These inappropriate nodes may be culled from the list manually and/or, where possible, using automated methods. An automated method may include, for example, removing any categories with no words and/or no words found in a customized or generic dictionary” Col. 11 Ln. 60-67 & Col. 12 Ln. 1-6); and
-cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106, e.g., tag 120 "Action and Adventure" [i.e. to correspond with the regenerated search navigation graph], a box 121 appears around the tag 120 and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively [i.e. cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph]” Col. 6 Ln. 57-63 and “The grouping of items from the list 300 may be accomplished using browse nodes associated with a browse tree, such as that discussed hereinbefore with FIGS. 5-7, and assigning a respective one of the tags 106 (FIG. 2) for each of the selected browse nodes” Col. 11 Ln. 27-31 and “a process 500 for generating the tag cloud 106 (FIG. 2) may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations [i.e. to correspond with the regenerated search navigation graph]” Col. 11 Ln. 46-49 and Fig. 2).
Gregov does not explicitly disclose the processing unit is further configured to, in response to a change in the items that includes a depletion of items associated with a particular attribute tag: regenerate the search navigation graph to correspond to the change in the items.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the processing unit is further being configured to, in response to a change in the items that includes a depletion of items associated with a particular attribute tag: regenerate the search navigation graph to correspond to the change in the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold [i.e. includes a depletion of items associated with a particular attribute tag:] at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the processing unit is further configured to, in response to a change in the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system [i.e. regenerate the search navigation graph to correspond to the change in the items]” [0036]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 1.
Regarding claim 23, Gregov in view of Pillarisetty teaches the method of claim 12. Gregov further discloses:
-regenerating the search navigation graph, wherein regenerating the search navigation graph comprises removing the node representing the particular attribute tag from the search navigation graph (Gregov, see at least: “if there is a browse node name that is not sufficiently descriptive, is uninformative, or is otherwise not appropriate to be included in the recommendations [i.e. regenerating the search navigation graph, wherein regenerating the search navigation graph] for the customer 10 as determined by the merchant 20, that node is also not used [i.e. comprises removing the node representing the particular attribute tag from the search navigation graph] and the next higher node is used instead as the selected node (provided it meets the other criteria discussed herein). For example, node names such as "16:10", "10.times. to 19.times.", "2 to 2.9 MP", "$100-199", may be nodes that are considered uninformative. These inappropriate nodes may be culled from the list manually and/or, where possible, using automated methods. An automated method may include, for example, removing any categories with no words and/or no words found in a customized or generic dictionary” Col. 11 Ln. 60-67 & Col. 12 Ln. 1-6); and
-causing the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106, e.g., tag 120 "Action and Adventure" [i.e. to correspond with the regenerated search navigation graph], a box 121 appears around the tag 120 and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively [i.e. causing the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph]” Col. 6 Ln. 57-63 and “The grouping of items from the list 300 may be accomplished using browse nodes associated with a browse tree, such as that discussed hereinbefore with FIGS. 5-7, and assigning a respective one of the tags 106 (FIG. 2) for each of the selected browse nodes” Col. 11 Ln. 27-31 and “a process 500 for generating the tag cloud 106 (FIG. 2) may start at a block 502 which obtains the recommend items list 300 with the recommended items 302 and the corresponding nodes 304 associations [i.e. to correspond with the regenerated search navigation graph]” Col. 11 Ln. 46-49 and Fig. 2).
Gregov does not explicitly disclose, in response to a change in the items that includes a depletion of items associated with a particular attribute tag: regenerating the search navigation graph to correspond to the change in the items.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of, in response to a change in the items that includes a depletion of items associated with a particular attribute tag: regenerating the search navigation graph to correspond to the change in the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold [i.e. includes a depletion of items associated with a particular attribute tag:] at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. in response to a change in the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system [i.e. regenerating the search navigation graph to correspond to the change in the items]” [0036]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 12.
Claims 4, 6-8, 15, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Gregov, in view of Pillarisetty, in further view of Subramanya et al. (US 2016/0063590 A1), hereinafter Subramanya.
Regarding claim 4, Gregov in view of Pillarisetty teaches the system of claim 3. Gregov further discloses:
-wherein the processing unit is further configured to generate the search navigation graph by: promoting a node of the search navigation template graph by identifying the node as representing an attribute tag that is common to child nodes of two or more parent nodes at a common hierarchical level (Gregov, see at least: “Referring to FIGS. 6 & 7, there may be two browse nodes that have the same name in different browse trees or different branches of a tree. For example, in the "Fiction" branch of the "Books" tree 600 there may be the leaf node 606 "Sci-Fi/Fantasy". Referring to FIG. 7, similarly, in a "DVDs" tree 700, having a root node 702, there may be a node 704 called "Sci-Fi/Fantasy". If the two nodes 606,704 both have at least three items associated therewith, there may be two browse nodes with the same name "Sci-Fi/Fantasy". In that case, the items associated with the two nodes 606,704 may be combined under the common node name "Sci-Fi/Fantasy" [i.e. promoting a node of the search navigation template graph by identifying the node as representing an attribute tag that is common to child nodes of two or more parent nodes at a common hierarchical level] for use in generating the tags 106 [i.e. wherein the processing unit is further configured to generate the search navigation graph by:] to avoid possible confusion of having two tags with the same name in the same cloud (discussed more hereinafter)” Col. 10 Ln. 40-53).
Gregov in view of Pillarisetty does not explicitly teach moving the identified common node to the common hierarchical level of the parent nodes.
Subramanya, however, teaches a product taxonomy for an inventory of products (i.e. abstract), including the known technique of moving the identified common node to the common hierarchical level of the parent nodes (Subramanya, see at least: “system 300 (FIG. 3) can generate dynamic product groups by compiling the most relevant products for the high-demand keyword clusters, which can beneficially meet the current online market demand. In several embodiments, system 300 (FIG. 3) can search the inventory of products using the high-demand keywords clusters to generate relevant item clusters … for each high-demand keyword clusters, system 300 (FIG. 3) can build a tree of the items in the relevant item cluster based on the classification of the items in existing product taxonomy 400 (FIG. 4)” [0048] and “each of the items in each node of tree 500 has a relevance score, based on its relevance to the high-demand keyword cluster. Based on this relevance score, system 300 (FIG. 3) can prune and/or suppress subtrees in tree 500 … if multiple child nodes at a same level under a parent node have relevance scores that are approximately evenly distributed, the child nodes, and any sub-nodes, can be eliminated, and the parent node can be made a super-node [i.e. moving the identified common node to the common hierarchical level of the parent nodes]. For example, if the relevance scores for items in nodes 42-44 are approximately uniformly distributed across nodes 42-44, which are the child nodes of parent node 38, system 300 (FIG. 3) can suppress nodes 42-44 and merge them into super-node 38” [0050] and Fig. 5 indicates the hierarchical level that has notes 42-44 is removed when these nodes are combined into node 38). This known technique is applicable to the system of Gregov in view of Pillarisetty as they share characteristics and capabilities, namely, they are directed to a product taxonomy for an inventory of products.
It would have been recognized that applying the known technique of moving the identified common node to the common hierarchical level of the parent nodes, as taught by Subramanya, to the teachings of Gregov in view of Pillarisetty would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such references into similar systems. Further, including the modification of moving the identified common node to the common hierarchical level of the parent nodes, as taught by Subramanya, into the system of Gregov in view of Pillarisetty would have been recognized by those of ordinary skill in the art as resulting in an improved system that would provide improved searching and/or browsing for the products (Subramanya, [0037]).
Regarding claim 6, the combination of Gregov/Pillarisetty/Subramanya teaches the system of claim 4. Gregov further discloses:
-wherein the processing unit is further configured to regenerate the search navigation graph to correspond to the change, and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106, e.g., tag 120 "Action and Adventure", a box 121 appears around the tag 120 [i.e. and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph] and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively [i.e. regenerate the search navigation graph to correspond to the change, and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph]” Col. 6 Ln. 57-63).
Gregov does not explicitly disclose, in response to a change in the items that changes the attribute tags associated with the items, regenerate the search navigation graph to correspond to the change in the items.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of, in response to a change in the items that changes the attribute tags associated with the items, regenerate the search navigation graph to correspond to the change in the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. in response to a change in the items that changes the attribute tags associated with the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system [i.e. regenerate the search navigation graph to correspond to the change in the items]” [0036]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 1.
Regarding claim 7, the combination of Gregov/Pillarisetty/Subramanya teaches the system of claim 6.
Gregov does not explicitly disclose the processing unit is further being configured to regenerate the search navigation graph in response to the change in the items by repeating the pruning, the shrinking, and the promoting.
Pillarisetty, however, teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the processing unit being configured to regenerate the search navigation graph in response to the change in the items by repeating the pruning, the shrinking, and the promoting (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated [i.e. by repeating the pruning, the shrinking, and the promoting] when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the processing unit is further configured to regenerate the search navigation graph in response to the change in the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system” [0036]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 1.
Regarding claim 8, the combination of Gregov/Pillarisetty/Subramanya teaches the system of claim 6. Gregov further discloses:
-a memory in communication with the processing unit, the memory being configured to store a copy of the search navigation graph after the search navigation graph is generated (Gregov, see at least: “Thus, the browse tree 400 may be viewed as a collection of categories, each category corresponding to one of the browse nodes 402-418 of the tree 400 and each of the browse nodes 402-418 being associated with one or more items. The merchant server 24 may store the information and relationships associated with one or more browse trees for all items sold by the merchant. Accordingly, the browse tree 400 may be used by the merchant website 22 to display categories or groups of items for the customer 10 to use while shopping or browsing the merchant website 22 as well as used to categorize and/or identify items for various uses [i.e. store a copy of the search navigation graph after the search navigation graph is generated]” Col. 9 Ln. 44-54 and “The window 102 may be displayed upon access of the web site or upon login by the customer 10 to the merchant's website 22, or at any other time. At the top of the window 102, is a main title header 110, which states, "Recommendations For You"” Col. 5 Ln. 38-42 and “Prior to the Customer 10 selecting one of the tags 106 in the tag cloud 104, the viewer 108 displays a default view of items, e.g., the "All Categories" tag items. In some embodiments, the default view for the viewer 108 may be the display of items associated with a tag having the most items, the items most relevant to the customer 10 [i.e. store a copy of the search navigation graph after the search navigation graph is generated], or any other criteria” Col. 7 Ln. 5-10 and “The computers, servers, and the like described herein have the necessary electronics, software, memory, [i.e. a memory in communication with the processing unit, the memory being configured to] storage, databases, firmware, logic/state machines, microprocessors, communication links, displays or other visual or audio user interfaces, printing devices, and any other input/output interfaces to perform the functions described herein and/or achieve the results described herein” Col. 4 Ln. 15-21).
Regarding claim 15, Gregov in view of Pillarisetty teaches the method of claim 14. Gregov further discloses:
-wherein generating the search navigation graph further comprises: promoting a node of the search navigation template graph by identifying the node as representing an attribute tag that is common to child nodes of two or more parent nodes at a common hierarchical level (Gregov, see at least: “Referring to FIGS. 6 & 7, there may be two browse nodes that have the same name in different browse trees or different branches of a tree. For example, in the "Fiction" branch of the "Books" tree 600 there may be the leaf node 606 "Sci-Fi/Fantasy". Referring to FIG. 7, similarly, in a "DVDs" tree 700, having a root node 702, there may be a node 704 called "Sci-Fi/Fantasy". If the two nodes 606,704 both have at least three items associated therewith, there may be two browse nodes with the same name "Sci-Fi/Fantasy". In that case, the items associated with the two nodes 606,704 may be combined under the common node name "Sci-Fi/Fantasy" [i.e. promoting a node of the search navigation template graph by identifying the node as representing an attribute tag that is common to child nodes of two or more parent nodes at a common hierarchical level] for use in generating the tags 106 [i.e. wherein generating the search navigation graph further comprises:] to avoid possible confusion of having two tags with the same name in the same cloud (discussed more hereinafter)” Col. 10 Ln. 40-53).
Gregov in view of Pillarisetty does not explicitly teach moving the identified common node to the common hierarchical level of the parent nodes.
Subramanya, however, teaches a product taxonomy for an inventory of products (i.e. abstract), including the known technique of moving the identified common node to the common hierarchical level of the parent nodes (Subramanya, see at least: “system 300 (FIG. 3) can generate dynamic product groups by compiling the most relevant products for the high-demand keyword clusters, which can beneficially meet the current online market demand. In several embodiments, system 300 (FIG. 3) can search the inventory of products using the high-demand keywords clusters to generate relevant item clusters … for each high-demand keyword clusters, system 300 (FIG. 3) can build a tree of the items in the relevant item cluster based on the classification of the items in existing product taxonomy 400 (FIG. 4)” [0048] and “each of the items in each node of tree 500 has a relevance score, based on its relevance to the high-demand keyword cluster. Based on this relevance score, system 300 (FIG. 3) can prune and/or suppress subtrees in tree 500 … if multiple child nodes at a same level under a parent node have relevance scores that are approximately evenly distributed, the child nodes, and any sub-nodes, can be eliminated, and the parent node can be made a super-node [i.e. moving the identified common node to the common hierarchical level of the parent nodes]. For example, if the relevance scores for items in nodes 42-44 are approximately uniformly distributed across nodes 42-44, which are the child nodes of parent node 38, system 300 (FIG. 3) can suppress nodes 42-44 and merge them into super-node 38” [0050] and Fig. 5 indicates the hierarchical level that has notes 42-44 is removed when these nodes are combined into node 38). This known technique is applicable to the method of Gregov in view of Pillarisetty as they share characteristics and capabilities, namely, they are directed to a product taxonomy for an inventory of products.
It would have been recognized that applying the known technique of moving the identified common node to the common hierarchical level of the parent nodes, as taught by Subramanya, to the teachings of Gregov in view of Pillarisetty would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such references into similar methods. Further, including the modification of moving the identified common node to the common hierarchical level of the parent nodes, as taught by Subramanya, into the method of Gregov in view of Pillarisetty would have been recognized by those of ordinary skill in the art as resulting in an improved method that would provide improved searching and/or browsing for the products (Subramanya, [0037]).
Regarding claim 17, the combination of Gregov/Pillarisetty/Subramanya teaches the method of claim 15. Gregov further discloses:
-regenerating the search navigation graph to correspond to the change, and causing the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph (Gregov, see at least: “When the customer 10 selects (or clicks on) one of the various tags 106, e.g., tag 120 "Action and Adventure", a box 121 appears around the tag 120 [i.e. and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph] and the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively [i.e. regenerating the search navigation graph to correspond to the change, and causing the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph]” Col. 6 Ln. 57-63).
Gregov does not explicitly disclose, in response to a change in the items that changes the attribute tags associated with the items, regenerating the search navigation graph to correspond to the change in the items.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of, in response to a change in the items that changes the attribute tags associated with the items, regenerating the search navigation graph to correspond to the change in the items (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. in response to a change in the items that changes the attribute tags associated with the items]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system [i.e. regenerating the search navigation graph to correspond to the change in the items]” [0036]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 12.
Regarding claim 19, the combination of Gregov/Pillarisetty/Subramanya teaches the method of claim 17. Gregov further discloses:
-regenerating the search navigation graph to remove the node representing the particular attribute tag causes the selectable icon corresponding to the particular attribute tag to become grayed-out in the search navigation bar (Gregov, see at least: “when an image in the viewer 108 or a tag in the tag cloud 104 is selected, the display is updated to display the associated image or tag with a box, an outline, a color, shading, shadow, or some type of highlighting or mark so that the selected status thereof is distinguishable from those images and tags that have not been selected [i.e. causes the selectable icon corresponding to the particular attribute tag to become grayed-out in the search navigation bar]” Col. 7 Ln. 42-47 and “The customer 10 can continue to click on tags and add to the images shown in the viewer 108. If the customer clicks on a tag a second time, the box around the tag is removed [i.e. regenerating the search navigation graph to remove the node representing the particular attribute tag] and the corresponding items are removed from the viewer 108” Col. 7 Ln. 34-38).
Gregov does not explicitly disclose the change in the items being a depletion of items associated with a particular attribute tag.
Pillarisetty further teaches a data structure storing a hierarchical data structure (i.e. abstract), including the known technique of the change in the items being a depletion of items associated with a particular attribute tag (Pillarisetty, see at least: “The hierarchical data structure 400 includes nodes 410, 420 that are tied to each other by connectors 430. The connectors 430 themselves may be customized to establish a relationship between information stored at the nodes 410, 420. For instance, a connector 430 between an offer node 410A and product node 410B may be configured to cause one or more nodes to be updated when another node is updated. For example, if a product is sold at a particular store location, an offer for the product may change, e.g., based on a change in availability or inventory location [i.e. wherein the change in the items is a depletion of items associated with a particular attribute tag]. In this way, the hierarchical data structure 400 may take advantage of clustering algorithms to maintain a dynamic and up-to-date representation of a global inventory system” [0036]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Gregov with Pillarisetty for the reasons identified above with respect to claim 12.
Examiner Note: A series of singular dependent claims is permissible in which a dependent claim refers to a preceding claim which, in turn, refers to another preceding claim.
A claim which depends from a dependent claim should not be separated by any claim which does not also depend from said dependent claim. It should be kept in mind that a dependent claim may refer to any preceding independent claim. In general, applicant's sequence will not be changed. See MPEP § 608.01(n).
Claims 5 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Gregov, in view of Pillarisetty, in further view of Subramanya, in further view of Pyati et al. (US 2019/0311301 A1), hereinafter Pyati.
Regarding claim 5, the combination of Gregov/Pillarisetty/Subramanya teaches the system of claim 4.
The combination of Gregov/Pillarisetty/Subramanya does not explicitly teach the processing unit being further configured to generate the search navigation graph by performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied.
Pyati, however, teaches sorting data into a hierarchical structure (i.e. [0063]), including the known technique of the processing unit being configured to generate the search navigation graph by performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied (Pyati, see at least: “Clustering methods can include k-means clustering, hierarchical clustering, density-based clustering, grid-based clustering, and variations of these algorithms. In k-means clustering, a number of n data points are partitioned into k clusters such that each point belongs to a cluster with the nearest mean. The algorithm proceeds by alternating steps, assignment and update [i.e. the processing unit is further configured to generate the search navigation graph by performing the pruning, the shrinking, and the promoting iteratively]. During assignment, each point is assigned to a cluster whose mean yields the least within-cluster sum of squares (WCSS) (e.g., the nearest mean). During update, the new means is calculated to be the centroids of the points in the new clusters. Convergence is achieved when the assignments no longer change [i.e. until a convergence condition is satisfied]. One variation of k-means clustering dynamically adjusts the number of clusters by merging and splitting clusters [i.e. performing the pruning, the shrinking, and the promoting] according to predefined thresholds” [0062] and “Hierarchical clustering methods sort data into a hierarchical structure (e.g., tree, weighted graph, etc.) based on a similarity measure. Hierarchical clustering can be categorized as divisive or agglomerate. Divisive hierarchical clustering involves splitting or decomposing “central” nodes of the hierarchical structure where the measure of “centrality” can be based on “degree” centrality, (e.g., a node having the most number of edges incident on the node or the most number of edges to and/or from the node) … Agglomerative clustering takes an opposite approach from divisive hierarchical clustering. Instead of beginning from the top of the hierarchy to the bottom, agglomerative clustering traverses the hierarchy from the bottom to the top. In such an approach, clustering may be initiated with individual nodes and gradually combine nodes or groups of nodes together to form larger clusters. Certain measures of the quality of the cluster determine the nodes to group together at each iteration [i.e. performing the pruning, the shrinking, and the promoting]” [0063]). This known technique is applicable to the system of the combination of Gregov/Pillarisetty/Subramanya as they share characteristics and capabilities, namely, they are directed to sorting data into a hierarchical structure.
It would have been recognized that applying the known technique of the processing unit being configured to generate the search navigation graph by performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied, as taught by Pyati, to the teachings of the combination of Gregov/Pillarisetty/Subramanya would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such references into similar systems. Further, including the modification of the processing unit being configured to generate the search navigation graph by performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied, as taught by Pyati, into the system of the combination of Gregov/Pillarisetty/Subramanya would have been recognized by those of ordinary skill in the art as resulting in an improved system that would allow for convergence to a steady state (Pyati, [0026]).
Regarding claim 16, the combination of Gregov/Pillarisetty/Subramanya teaches the method of claim 15.
The combination of Gregov/Pillarisetty/Subramanya does not explicitly teach generating the search navigation graph comprising performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied.
Pyati, however, teaches sorting data into a hierarchical structure (i.e. [0063]), including the known technique of generating the search navigation graph comprising performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied (Pyati, see at least: “Clustering methods can include k-means clustering, hierarchical clustering, density-based clustering, grid-based clustering, and variations of these algorithms. In k-means clustering, a number of n data points are partitioned into k clusters such that each point belongs to a cluster with the nearest mean. The algorithm proceeds by alternating steps, assignment and update [i.e. the processing unit is further configured to generate the search navigation graph by performing the pruning, the shrinking, and the promoting iteratively]. During assignment, each point is assigned to a cluster whose mean yields the least within-cluster sum of squares (WCSS) (e.g., the nearest mean). During update, the new means is calculated to be the centroids of the points in the new clusters. Convergence is achieved when the assignments no longer change [i.e. until a convergence condition is satisfied]. One variation of k-means clustering dynamically adjusts the number of clusters by merging and splitting clusters [i.e. performing the pruning, the shrinking, and the promoting] according to predefined thresholds” [0062] and “Hierarchical clustering methods sort data into a hierarchical structure (e.g., tree, weighted graph, etc.) based on a similarity measure. Hierarchical clustering can be categorized as divisive or agglomerate. Divisive hierarchical clustering involves splitting or decomposing “central” nodes of the hierarchical structure where the measure of “centrality” can be based on “degree” centrality, (e.g., a node having the most number of edges incident on the node or the most number of edges to and/or from the node) … Agglomerative clustering takes an opposite approach from divisive hierarchical clustering. Instead of beginning from the top of the hierarchy to the bottom, agglomerative clustering traverses the hierarchy from the bottom to the top. In such an approach, clustering may be initiated with individual nodes and gradually combine nodes or groups of nodes together to form larger clusters. Certain measures of the quality of the cluster determine the nodes to group together at each iteration [i.e. performing the pruning, the shrinking, and the promoting]” [0063]). This known technique is applicable to the method of the combination of Gregov/Pillarisetty/Subramanya as they share characteristics and capabilities, namely, they are directed to sorting data into a hierarchical structure.
It would have been recognized that applying the known technique of generating the search navigation graph comprising performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied, as taught by Pyati, to the teachings of the combination of Gregov/Pillarisetty/Subramanya would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such references into similar methods. Further, including the modification of generating the search navigation graph comprising performing the pruning, the shrinking, and the promoting iteratively until a convergence condition is satisfied, as taught by Pyati, into the method of the combination of Gregov/Pillarisetty/Subramanya would have been recognized by those of ordinary skill in the art as resulting in an improved method that would allow for convergence to a steady state (Pyati, [0026]).
Examiner Note: While no claim set was received in conjunction with the Remarks filed 02/25/2026, based on claim 1 presented on pages 2-3 of the remarks, as well as, the Applicant not indicating any amended claims under the “status of the claims” on page 2 of the remarks, Examiner assumes that the current claims are the same as those previously presented on 11/12/2025.
Response to Arguments
Rejections under 35 U.S.C. §101
Applicant argues that, much of what the Patent Office has asserted falls within the "certain methods of organizing human activity," as shown via the bold text above, does not fall within the sub-groupings enumerated in MPEP 2106.04(a)(2)(ii), which are fundamental economic principles or practices, commercial or legal interactions, and managing personal behavior and relationships or interactions between people. Looking at claim 1, contrary to the position taken by the Patent Office, at least the recited features of obtaining attribute tags associated with items and generating a search navigation graph based on a search navigation template graph, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag and wherein the search navigation graph includes only nodes of the search navigation template graph representing the attribute tags associated with the items do not fall within any of the enumerated sub-groupings of fundamental economic principles or practices, commercial or legal interactions, and
managing personal behavior and relationships or interactions between people. As stated in
MPEP 2106.04(a)(2)(11), the certain methods of organizing human activity grouping of abstract ideas is not to be expanded beyond these enumerated sub-groupings except in rare circumstances (Remarks, pages 2-3).
Examiner respectfully disagrees. The recited features of obtaining attribute tags associated with items and generating a search navigation graph based on a search navigation template graph, the search navigation graph comprising a hierarchical graph wherein each node in the search navigation graph represents the respective attribute tag and wherein the search navigation graph includes only nodes of the search navigation template graph representing the attribute tags associated with the items fall within the “Certain Methods of Organizing Human Activity” groupings of abstract ideas, enumerated in MPEP 2106.04(a), as they cover a commercial interaction in that they encompasses advertising, and marketing or sales activities. For instance, these features search a hierarchical graph of attribute tags of an item in order to provide relevant items available for purchase for buyer (i.e. advertising, and marketing or sales activities). Accordingly, the claims are directed to an abstract idea.
Applicant further argues that the rationale given by the Patent Office in the Final Office Action and reiterated in the current Office Action for grouping the aforementioned features of claim 1 (all bolded text in claim 1 above) into the certain methods of organizing human activity grouping of abstract ideas is that these features "are processes that, under their broadest reasonable interpretation, cover a commercial interaction."1 The Patent Office continued by stating "nothing in the claim element precludes the step from practically being performed by people."2 However, first, the Patent Office cannot show that these features of claim 1 amount to "commercial interactions" simply by saying that these features could be practically performed by people as there are many types of human activities other than commercial interactions. The Patent Office must also show that these recited features of claim 1 are directed to commercial interactions. The examples of commercial interactions given in MPEP 2106.04(a)(2)(11) include advertising and marketing or sales activities or behaviors. Obtaining attribute tags associated with items and generating a search navigation graph are not advertising or marketing or sales activities and are thus not commercial interactions. Second, contrary to the Patent Office's assertion, the aforementioned features of claim 1 cannot practically be performed by people. A person or people cannot practically perform such actions for any reasonable environment which includes many items, many tags, and many detected events. In fact, it would be impractical for a person(s) to obtain attribute tags associated to items and generating the recited search navigation graph for even a small number of items, tags, and events in any reasonable amount of time that would be beneficial to a person to whom the recited search navigation bar is to be displayed (Remarks, pages 3-4).
Examiner respectfully disagrees. Examiner has shown that the recited features fall within the “Certain Methods of Organizing Human Activity” groupings of abstract ideas as they encompass the advertising, and marketing or sales activities bolded in the recited limitations. Obtaining attribute tags associated with items and generating a search navigation graph are advertising, and marketing or sales activities as they are used to provide relevant items available for purchase for buyer. Additionally, while applying generic computer components would be faster, a human can still practically perform these steps and there is no required time constraint recited on these steps being performed. Accordingly, the claims are directed to an abstract idea.
Applicant further argues that, if the Patent Office believes that the present claims qualify as a one of the "rare circumstances" in which the certain methods of organizing human activity grouping of abstract ideas should be expanded beyond the aforementioned enumerated sub-groupings, then the Patent Office is reminded of the requirements of MPEP 2106.04(a)(3), which have not been satisfied in the present case (Remarks, page 5).
Examiner has not indicated that the recited claims qualify as a one of the "rare circumstances." As detailed in response to the above arguments, the recited claims fall within the “Certain Methods of Organizing Human Activity” groupings of abstract ideas, enumerated in MPEP 2106.04(a), as they cover a commercial interaction in that they encompasses advertising, and marketing or sales activities. Accordingly, the claims are directed to an abstract idea.
Applicant further argues that, in response to the arguments above presented in Applicant's response to the previous Final Office Action, the Patent Office asserted that the aforementioned recited features of claim 1 "fall within the 'Certain Methods of Organizing Human Activity' groups of abstract ideas, enumerated in MPEP 2106.04(a), as they cover a commercial interaction in that they encompass advertising, and marketing or sales activities" in that "these features search a hierarchical graph of attribute tags of an item in order to provide relevant items available for purchase for buyer (i.e., advertising, and marketing or sales activities )." Applicant respectfully disagrees. MPEP 2106.04(a) explicitly requires that the claim limitations themselves must fall within the grouping of abstract ideas. It is not sufficient for the claim limitations to "encompass advertising, and marketing sales activities." Further, the Patent Office's statement that the recited features are performed "in order to provide relevant items available for purchase for buyer" is not in fact a limitation of the claim. Again, it is not sufficient that the claimed limitations could be used for this purpose. The claim limitations themselves must fall within the grouping of abstract ideas. The fact that the claimed limitations themselves must fall within the grouping of abstract ideas is supported by the examples given in MPEP 2106.04(a)(2). MPEP 2106.04(a)(2) provides details regarding the abstract idea groups. Therefore, even if the claim limitations at issue could be used for a commercial interaction, this is not sufficient to say that claim 1 falls with the judicial exception of certain methods of organizing human activity. Since the claim limitations themselves do not fall within the grouping of certain methods of organizing human activity, Applicant respectfully requests that the rejection of claim 1 under 35 USC 101 be withdrawn (Remarks, pages 5-6).
Examiner respectfully disagrees. Examiner has shown that the recited features fall within the “Certain Methods of Organizing Human Activity” groupings of abstract ideas as they encompass the advertising, and marketing or sales activities bolded in the recited limitations in that they recite the abstract idea of generating a search navigation graph in response to an event, the search navigation graph including nodes that represent attribute tags associated with items. For instance, the claim in Ultramercial, Inc. v. Hulu (cited as an example in MPEP 2106.04(a)(2)) do not explicitly recite “displaying an advertisement (ad) in exchange for access to copyrighted media,” however, it was still concluded that the claims recited the abstract idea of “displaying an advertisement (ad) in exchange for access to copyrighted media.” Accordingly, the claims are directed to an abstract idea.
Applicant further argues that, in response to Applicant's argument above relate to the Patent Office's statement that "nothing in the claim element precludes the step from practically being performed by people," the Patent Office stated that "while applying a generic computer components would be faster, a human can still practically perform these steps and there is no required time constraint recited on these steps being performed." Applicant respectfully disagrees. The term "practically" inherently requires a time constraint. If an operation can be performed by a human in 24 hours but doing that operation in 24 hours would render the operation useless for its intended purpose, then it cannot be said to "practically" performed in the human mind. Such is true in the case of claim 1. As such, the steps of claim 1 cannot practically be performed in the human mind (Remarks, page 7).
Examiner respectfully disagrees. Applicant appears to be confusing efficiency with impracticality. For instance MPEP 2106.04(a)(2)(III)(A) describes the example of Electric Power Group v. Alstom in which it was determined that "collecting information, analyzing it, and displaying certain results of the collection and analysis" can be can practically be performed in the human mind. Accordingly, the claims are directed to an abstract idea.
Applicant further argues that, under Step 2A, Prong Two, the Patent Office asserted that claim 1 does not recite additional elements that integrate the exception into a practical application of the exception. Applicant respectfully disagrees. As argued below with respect to Step 2B, claim 1 includes additional elements that integrate the exception into an improvement to the technology or technical field of attribute-based searching of a collection of items. The arguments below in this regard are equally applicable here to the analysis of Step 2A, Prong Two. Since claim 1 includes additional elements that integrate the exception into an improvement to the technology or technical field of attribute-based searching of a collection of items, claim 1 integrates the judicial exception into a practical application and, as such, claim 1 is directed to patentable subject matter under 35 U.S.C. 101 (Remarks, pages 7).
Examiner respectfully disagrees. Attribute-based searching of a collection of items is not a technology or technical field. Additionally, the additional elements recited in the claims are insufficient to integrate the abstract idea into a practical application because the claims fail to reflect an improvement in the functioning of a computer or an improvement to another technology or technical field. Accordingly, the claims are not integrated into a practical application.
Applicant further argues that, under Step 2B, claim 1 includes "significantly more" under Step 2B of the test for subject matter eligibility. In Applicant's Response to the Office Action mailed May 15, 2025 (hereinafter "the "Previous Response"), Applicant argued that, in regard to claim 1 (and using the current amended claim language), the recited elements are an improvement to the technology or technical field of attribute-based searching of a collection of items. In response to Applicant's previous argument, the Patent Office asserted that "[m]aking searching faster and more efficient by using attribute-based searching is a business improvement, not a technological improvement as the technology itself (e.g., the computer, the interface, etc.) is not improved" and "attribute-based searching is not a technical field. Applicant respectfully disagrees. First, improving a computer's ability to provide faster and more efficient attribute-based searching is a technological improvement as the technology of computer-implemented attribute-based searching is improved. Second, computer-implemented attribute-based searching is a technical field. Importantly, an improvement to a technology or technical field is not limited to an improvement to the computer itself as demonstrated by McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-16, 120 USPQ2d 1091, 1102-03 (Fed. Cir. 2016) where the court found that claims to automatic lip synchronization and facial expression animation were directed to an improvement in computer-related technology and not an abstract idea. Thus, there is no requirement that the improvement be an improvement to the computer itself. An improvement to a computer-related technology is sufficient. In the present case, computer-implemented attribute-based searching as claimed in claim 1 is a computer-related technology in the same manner that the automatic lip synchronization and facial expression animation in McRO was found to be directed to a computer-related technology. Therefore, contrary to the assertion made by the Patent Office, computer implemented attribute-based searching is a computer-related technology and a technical field and, as such, the claimed invention of claim 1 provides an improvement to a technology or technical field. Thus, the aforementioned elements of claim 1 amount to "significantly more" than the judicial exception and, therefore, claim 1 is directed to statutory subject matter under 35 USC 101. Applicant respectfully requests that the rejection of claim 1 under 35 USC 101 be withdrawn (Remarks, pages 8-9).
Examiner respectfully disagrees. As previously described, making searching faster and more efficient by using attribute-based searching is a business improvement, not a technological improvement as the technology itself (e.g. the computer, the interface, etc.) is not improved. Additionally, attribute-based searching is not a technical field as, while the claims utilize generic computer components, attribute-based searching itself does not require any technological components. When describing “Improvements to any technology or technical field” MPEP 2106.05(a)(II) states: “To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology.”
Furthermore, in McRO the claims “focused on a specific asserted improvement in computer animation, i.e., the automatic use of a particular type” [see McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299, 120 U.S.P.Q.2d 1091 (Fed. Cir. 2016) page 24]. The claims were found eligible because of a specific improvement in computer animation (i.e. a problem rooted in technology). This is not the case with the claimed invention. Unlike in McRO, the claimed invention fails to reflect an improvement in the functioning of a computer or an improvement to another technology or technical field. Accordingly, the claims are not integrated into a practical application.
Applicant further argues that just as claims in McRO which are focused on a specific asserted improvement in computer animation are "rooted in technology," claim 1 is directed to computer-implemented attribute-based searching which is also a problem rooted in technology for at least the reason that it is "computer-implemented" (Remarks, page 10).
Examiner respectfully disagrees. As described above, McRO the claims “focused on a specific asserted improvement in computer animation, i.e., the automatic use of a particular type” [see McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299, 120 U.S.P.Q.2d 1091 (Fed. Cir. 2016) page 24]. The claims were found eligible because of a specific improvement in computer animation (i.e. a problem rooted in technology). Merely performing the abstract idea on a computer fails to reflect an improvement in the functioning of a computer or an improvement to another technology or technical field as the technology itself is not improved, it is merely applied. Accordingly, the claims are not integrated into a practical application and do not amount to significantly more.
Applicant further references Ex parte Hannun 2018-003323 stating that “The mathematical algorithm or formula, however, is not recited in the claims. As such, under the recent Memorandum, the claims do not recite a mathematical concept.” Applying this principle to the present case, no commercial transaction or legal obligation is recited in claim 1, and therefore, claim 1 does not recite the judicial exception (Remarks, page 10).
Examiner respectfully disagrees. Examiner points out that this case is nonprecedential. Regardless, unlike Ex parte Hannun, the commercial interaction that the amended claims are directed to is recited in the claims (see responses to the arguments above). Accordingly, the claims are ineligible.
Applicant further argues that, regarding claims 2, 3, and 4, the Patent Office responded to Applicant's previous arguments regarding the rejections of claims 2, 3, and 4 in the same manner as it responded to Applicant's previous arguments regarding the rejection of claim 1 (i.e., by asserting that "[m]aking searching faster and more efficient by using attribute-based searching is a business improvement, not a technological improvement as the technology itself (e.g., the computer, the interface, etc.) is not improved" and "attribute-based searching is not a technical field." For the same reasons argued above with respect to claim 1, claims 2, 3, and 4 are directed to statutory subject matter under 35 USC 101 because computer-implemented attribute-based searching is a computer-related technology and a technical field and claims 2, 3, and 4 provide the previously argued improvements to computer-implemented attribute-based searching. Applicant respectfully requests that the rejection of claims 2, 3, and 4 under 35 USC 101 be withdrawn (Remarks, page 11).
Examiner respectfully disagrees. As discussed in response to the arguments referring to claim 1, the claims fail to reflect an improvement in the functioning of a computer or an improvement to another technology or technical field. Accordingly, the claims are ineligible.
Applicant further argues that claims 12 and 21 include features similar to those of claim 1 and as such contain patent subject matter under 35 USC 101 for at least the same reasons argued above with respect to claim 1 (Remarks, page 11).
Examiner respectfully disagrees. As discussed in response to the arguments above, claim 1 is not eligible. Accordingly, claims 12 and 21 are not eligible.
Applicant further argues Ex Parte Desjardins 2024-000567, where the Appeals Review Panel of the Patent Trial and Appeal Board at the USPTO found that claims that are, at least for purposes of an analysis under 35 USC 101, similar to the claims of the present application to be patent eligible. Claim 1 in Ex Parte Desjardins was directed to a "computer-implemented method of training a machine learning model" but otherwise gave no details of how a computer aids in the method other than performing the recited functions. In that case, the Appeals Review Panel found that the claims recited additional elements that reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field. The Appels Review Patent based its decision on Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) which "recognized that '[m]uch of the advancement made in computer technology consists of improvements to software that, by their very nature, many not be defined by particular physical features but rather by logical structures and processes.' 822 F.3d at 1339." The Appeals Review Panel continued by stating that "[m]oreover, because '[s]oftware can made non-abstract improvements to computer technology, just as hardware improvements can,' the Federal Circuit held that eligibility determination should tum on whether 'the claims are directed to an improvement to computer functionality versus being directed to an abstract idea.' Id. at 1336." The claims of the present application, like the claims at issue in Ex Parte Desjardins, provide an improvement in the functioning of a computer, or an improvement to other technology or technical field (as argued above) and, as such, integrate an abstract idea into a practical application. Computer-implemented attributed based searching 1s a technology or technical field and the claims are directed to an improvement to this technology or technical field. As such, just like Ex Parte Desjardins or Enfish, the claimed invention reflects an improvement in the functioning of a computer or an improvement to another technology or technical field (Remarks, pages 11-12).
Examiner respectfully disagrees. In Ex Parte Desjardins the claims were not found eligible because they computer implemented, rather, the recited claims train the machine learning model in such a way that it “allows the model to preserve performance on earlier tasks even as it learns new ones, directly addressing the technical problem of 'catastrophic forgetting' in continual learning systems" (see Ex Parte Desjardins). The machine learning itself was improved. In Enfish the storing of tabular data is specifically directed to a self-referential table. Thus, the claims were “directed to a specific improvement to the way computers operate,” rather than utilizing a computer as a means for implementing an abstract idea. Id at 1336. No such technological improvement is recited in the current claims. Merely performing the abstract idea on a computer fails to reflect an improvement in the functioning of a computer or an improvement to another technology or technical field as the technology itself is not improved, it is merely applied. Accordingly, the claims are ineligible.
Rejections under 35 U.S.C. §103
Applicant argues that the combination of Gregov and Pillarisetty fails to teach at least (C) and (D). In regard to (C) above, claim 1 explicitly requires both: (1) a search navigation graph comprising a hierarchical graph where each node in the search navigation graph represents a respective attribute tag and (2) a search navigation template graph, where the search navigation graph is generated based on the search navigation template graph. As argued in the Previous response, the tag cloud of Gregov is not a search navigation graph comprising a hierarchical graph where each node in the search navigation graph represents a respective attribute tag as required by claim 1. In particular, the tag cloud in Gregov is simply a collection of tags descriptive of respective subsets of the recommended items. The tag cloud of Gregov fails to include a hierarchical graph as required by claim 1. For instance, the user in Gregov cannot select a certain tag in the tag cloud to see the child tags of the selected tag. In Gregov, when the user selects a certain tag, the recommended items associated to that selected tag are displayed to the user. In contrast, the recited search navigation graph has a hierarchical structure, which when displayed in the navigation search bar in accordance with the teachings of the present application, enables a user to navigate through the hierarchical structure of the search navigation graph to further refine the user's search. In other words, in Gregov, the browse tree (which is read as the recited search navigation template graph of claim 1) is used to generate an entirely new structure, i.e., the tag cloud of Gregov, that represents a set of recommended items for the user. In contrast, in claim 1, the generated search navigation graph is a simplified/reduced version of a larger search navigation template graph that includes only those nodes that represent attribute tags associated with certain items. The Patent Office's remarks relate only to the browse tree of Gregov, which is read by the Patent Office as the recited search navigation template graph, and are not applicable to the tag cloud of Gregov, which is read by the Patent Office as the recited search navigation graph. The Patent Office has failed to show that, and indeed Gregov fails to teach that, the generated tag cloud of Gregov comprises a hierarchical graph where each node in the search navigation graph represents a respective attribute tag as required by claim 1. Further, The Patent Office is conflating the recited search navigation template graph and the recited search navigation graph, which are two distinct hierarchical graphs. The single hierarchical graph in Gregov cannot be both the recited search navigation template graph and the recited search navigation graph (which is a reduced version of the search navigation template graph including only nodes of the search navigation template graph representing attribute tags associated with the items). Pillarisetty does not cure this, because it concerns backend inventory indexing ( offer/product/store nodes and connectors) rather than generation or pruning of UI attribute-tag graphs. (Remarks, pages 12-15).
Examiner respectively disagrees. As previously explained, Gregov discloses that the nodes in the graph have a root level with corresponding lower levels that are more specific categories [i.e. the search navigation graph comprising a hierarchical graph] (see Gregov, Col. 12 Ln. 32-38). Additionally, Figs. 5-6 of Gregov clearly indicate that the search navigation graph is a hierarchical graph. Examiner is not equating the tag cloud itself to the search navigation graph, rather, the node associations of the recommended items (which is a hierarchical graph as indicated by Figs. 5-6) that are used to generate the tag cloud is the search navigation graph. Furthermore, Gregov discloses that the recommended item list corresponds to node associations from the stored inventory hierarchical graph that contains all of the items in the inventory (see Gregov, Col. 11 Ln. 46-66 and Fig. 4-6). In other words, the larger navigational graph, from which the smaller graph of the node associations of the recommended items is derived from, is the search navigation template graph. Applicant described in the current and previous arguments that “in claim 1, the generated search navigation graph is a simplified/reduced version of a larger search navigation template graph that includes only those nodes that represent attribute tags associated with certain items,” which also describes the disclosure of Gregov. Accordingly, the cited references teach the current claims.
Applicant further argues that the Office Action's position that the "node associations of the recommended items" in Gregov constitute a hierarchical graph usable as the claimed "search navigation graph" is unsupported by the cited disclosure of Gregov. As the Office Action acknowledges, the only hierarchical graph actually disclosed in Gregov is the browse tree shown in Figures 5 and 6 of Gregov, which is a merchant-defined product taxonomy ("a hierarchical tree arrangement of browse nodes 402-418, having a plurality of different levels 420"). However, that browse tree is what the Patent Office simultaneously relies upon as the search navigation template graph, and thus it cannot also serve as the separate, derived search navigation graph required by the claims. The Patent Office's assertion that "the node associations of the recommended items ... used to generate the tag cloud is the search navigation graph" (Office Action at pp. 60-61) is not supported by Gregov. In Gregov, "node associations" merely refer to the fact that recommended items are linked to nodes in the browse tree through metadata ("obtains the recommended items list 300 with the recommended items 302 and the corresponding nodes 304 associations"). Nowhere does Gregov describe these associations as forming a hierarchical graph, nor does it state that parent-child relationships of the browse tree are preserved or represented in any data structure generated from recommended items. Rather, Gregov uses these associations only to build a flat tag cloud of category labels ("the tag cloud 106 . . . categories or tags 106 displayed having a predetermined quantity identifier 111"). The tag cloud is explicitly non-hierarchical: selecting a tag displays items in the viewer ("the viewer 108 displays ... recommended items in the selected tag") and does not reveal child tags or any hierarchical navigation structure. Accordingly, the "node associations" cited by the Examiner are merely item-to-category metadata and do not constitute a hierarchical graph, much less the distinct, reduced navigation graph generated from the template graph required by claim 1. Because Gregov discloses only (1) a single hierarchical browse tree (the alleged template) and (2) a flat tag cloud, it does not teach or suggest the claimed separation between a search navigation template graph and a search navigation graph generated by reducing the template to include only nodes representing attribute tags associated with the items. The Patent Office's reasoning therefore conflates two distinct claim-mandated structures and cannot satisfy element (C) (Remarks, pages 15-16).
Examiner respectively disagrees. Gregov discloses that the recommended item list corresponds to node associations from the stored inventory hierarchical graph (i.e. the browse nodes) that contains all of the items in the inventory (see Gregov, Col. 11 Ln. 46-66 and Fig. 4-6). In other words, the larger navigational graph, from which the smaller graph of the node associations of the recommended items is derived from, is the search navigation template graph. Applicant described in the current and previous arguments that “in claim 1, the generated search navigation graph is a simplified/reduced version of a larger search navigation template graph that includes only those nodes that represent attribute tags associated with certain items,” which also describes the disclosure of Gregov. Additionally, the node table of Fig. 4 shows that the nodes of the recommended items are organized as browse nodes (i.e. indicating a position in a hierarchical browse tree) such as items 1-3 being node 1 (further see Col. 11 Ln. 32-40 of Gregov which described this aspect of Fig. 4). Accordingly, the cited references teach the current claims.
Applicant further argues that, in regard to (D), in the Previous Response, Applicant argued that Gregov fails to teach causing a search navigation bar in a user interface to be displayed with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph. The tag cloud of Gregov includes user-selectable icons/tags for tags/categories from the browse tree. As discussed above, the Patent Office is reading the browse tree as the recited search navigation template graph. Thus, at most, the cited teachings of Gregov teach that the displayed tags in the tag cloud (read as the recited search navigation group) correspond to different tags/categories in the browse tree (read as the recited search navigation template graph). This is different from what is required by claim 1 where the selectable icons each represent a respective attribute tag represented by a respective node of the search navigation graph (read as the tag cloud of Gregov). As such, Gregov fails to teach element (D) of claim 1. The Patent Office is conflating the recited search navigation template graph and the recited search navigation graph, which are two distinct hierarchical graphs. The single hierarchical graph in Gregov cannot be both the recited search navigation template graph and the recited search navigation graph (which is a reduced version of the search navigation template graph including only nodes of the search navigation template graph representing attribute tags associated with the items). Further, the "node associations" of Gregov cannot be read as a hierarchical graph such as the search navigation graph, as argued above with respect to element (C). As such, Gregov fails to teach the claimed feature of causing a search navigation bar in a user interface to be displayed with selectable icons, the selectable icons each being a representation of a respective attribute tag represented by a respective node of the search navigation graph. Pillarisetty fails to correct the aforementioned deficiencies of Gregov (Remarks, pages 16-17).
Examiner respectively disagrees. As previously explained, Gregov discloses that the GUI in Fig. 2 displays selectable tag icons [i.e. the selectable icons] for each browse node that represent different tag categories [i.e. being a representation of a respective attribute tag] from the browse tree in the tag cloud such as “Action & Adventure,” “Picture Books,” etc. [i.e. represented by a respective node of the search navigation graph] (see Gregov, Col. 5 Ln. 59-67 & Col. 6 Ln. 1-2, Col. 6 Ln. 48-55, and Fig. 2). Additionally, Gregov discloses that the recommended item list corresponds to node associations from the stored inventory hierarchical graph (i.e. the browse nodes) that contains all of the items in the inventory (see Gregov, Col. 11 Ln. 46-66 and Fig. 4-6). The search navigation template graph and the recited search navigation graph are separate graphs; the larger navigational graph, from which the smaller graph of the node associations of the recommended items is derived from, is the search navigation template graph. Applicant describes that the recited search navigation graph is a reduced version of the search navigation template graph including only nodes of the search navigation template graph representing attribute tags associated with the items; this is what is described the disclosure of Gregov. Furthermore, the node table of Fig. 4 shows that the nodes of the recommended items are organized as browse nodes (i.e. indicating a position in a hierarchical browse tree) such as items 1-3 being node 1 (further see Col. 11 Ln. 32-40 of Gregov which described this aspect of Fig. 4). Accordingly, the cited references teach the current claims.
Applicant further argues that, in regard to claim 3, the combination of Gregov and Pillarisetty fails to teach the recited feature of "shrinking the search navigation template graph by identifying a hierarchical level in the search navigation template graph that contains only a single node and removing the identified hierarchical level from the search navigation template graph." In regard to claim 3, Applicant previously argued that the cited disclosure of Gregov relied on by the Patent Office in the rejection of claim 3 relates to populating or creating the node table that lists the names of the lowest level nodes having at least three recommended items for the user. However, Gregov fails to teach shrinking of the browse tree (which the Patent Office is reading as the recited search navigation template graph) by identifying and removing a hierarchical level in the browse tree that contains only a single node. The teachings of Gregov are completely different than what is required by claim 3. Gregov does not consider the number of nodes at a certain hierarchical level of the browse tree at all. Rather, Gregov considers the number of actual recommended products or items associated to a certain node in the browse tree. In Gregov, if a certain node is associated to less than three recommended products or items, then the next higher node in the browse tree that is associated with three or more recommended products or items is instead used for the generated tag cloud. Gregov fails to teach identifying a hierarchical level in the browse tree that includes a single node and then removing that hierarchical level as required by claim 3. Pillarisetty fails to correct this deficiency of Gregov. The Office Action equates Gregov's rule "if a node has fewer than three items, do not use that node and use the next higher node instead" with removing a level that contains only one node. That is incorrect. Gregov evaluates the number of items per node and may still leave multiple nodes at the same level; it never identifies a level that has only one node nor removes the level. The recited features of claim 3 operate on level cardinality, not item counts per node. No cited passage in Gregov (or Pillarisetty) identifies a hierarchical level that contains only a single node and removes that level; therefore, the combination of Gregov and Pillarisetty fails to teach the features of claim 3. Pillarisetty fails to correct this deficiency of Gregov (Remarks, pages 17-19).
Examiner respectively disagrees. As previously explained, Gregov discloses that if a lower level node has less than three items [i.e. by identifying a hierarchical level in the search navigation template graph that contains only a single node], that lower level node is not used and the next higher level node is used instead as the selected node [i.e. shrinking the search navigation template graph and removing the identified hierarchical level from the search navigation template graph] (see Gregov, Col. 11 Ln. 46-58). Gregov additionally indicates in Fig. 5 that the lower level 3 only contains one node (i.e. the removal of the lower level node removes the entire level). In other words, a node having only one item, as one is less than three, the node, and thus the node’s corresponding level, is not used and only the level of nodes above it is used. The number of nodes at a certain hierarchical level of the browse tree is considered as the nodes associated with number of recommended products are in the browse tree. Accordingly, the cited references teach the current claims.
Applicant further argues that, in regard to claim 9, the combination of Gregov and Pillarisetty fails to teach the recited feature of the processing unit is further configured to "apply a filter to the items, regenerate the search navigation graph to correspond to the filtered items, and cause the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph." The Patent Office's characterization of Gregov emphasized above is incorrect. Looking at Figure 2 of Gregov, the user interface includes a tag cloud section (104) in which the generated tag cloud is presented and a recommendation window (102) in which the recommended products or items for the selected tag in the tag cloud are presented. Gregov teaches that "[w]hen the customer 10 selects ( or clicks on) one of the various tags 106, e.g., tag 120 'Action and Adventure', ... the viewer 108 displays a series of five adjacent thumbnail images 132-140 of the items in five corresponding adjacent locations 142-150, indicative of the first five recommended items in the selected tag or category 120, respectively." 17 In other words, contrary to the Patent Office's assertation, the tag cloud presented in the tag cloud section (104) (which the Patent Office is reading as the recited search navigation graph) is not regenerated to only include the nodes from the selected category. Rather, the thumbnail images (132-140) in the recommendation window (102) are updated to represent the first five recommended items associated to the selected tag in the tag cloud. Therefore, contrary to the position taken by the Patent Office, Gregov fails to teach the recited feature of claim 9 which requires the search navigation group (read as the tag cloud of Gregov) to be regenerated to correspond to the filtered items and causes the search navigation bar on the user interface to be updated to correspond with the regenerated search navigation graph. Pillarisetty fails to correct this deficiency of Gregov. The Office Action asserts that selecting "Action & Adventure" in Gregov regenerates the "search navigation graph" and updates the UI accordingly. The cited text in Gregov, however, explains that selection of a tag updates the item viewer (displaying the first five recommended items) while the tag cloud itself persists. There is no disclosure in Gregov that the set of displayed tags is regenerated to reflect the filtered items, nor that a navigation bar ( of tags) is updated. Claim 9 expressly requires regeneration of the navigation graph to correspond to the filtered items and updating of the navigation bar to reflect the regenerated graph-features not taught or suggested by Gregov or Pillarisetty (Remarks, pages 19-21).
Examiner respectively disagrees. As has been established in the citations for claim 1 (from which claim 9 depends), Gregov discloses that the grouping of items from the recommended item list is accomplished using browse nodes associated with a browse tree and that the tag cloud displayed to the user is created based on the recommended items from the browse tree (see Gregov, Col. 11 Ln. 27-31, Col. 11 Ln. 46-49, Col. 9 Ln. 31-47, and Fig. 2). Gregov further discloses that, when the customer selects one of the various tags, such as the "Action and Adventure" tag, the interface is updated to display newly recommended items in the selected category (see Gregov, Col. 6 Ln. 57-63). In other words, the search navigation graph of nodes used for the recommended items is regenerated to only include the nodes from the selected category. Additionally, Examiner is not equating the tag cloud itself to the search navigation graph, rather, the smaller graph of the node associations of the recommended items that is created in the node table of Fig. 4 is the search navigation graph. Furthermore, Gregov discloses that, when the user selects the "Action and Adventure," a box appears around said tag (see Gregov, Col. 6 Ln. 57-63 and Fig. 2). This appearance of a box causes the search navigation bar to be updated to correspond with the regenerated search navigation graph as it now displays the categorical focus of the regenerated search navigation graph. Accordingly, the cited references teach the current claims.
Applicant further argues that claims 2 and 11 depend from claim 1 and as such are allowable at least by virtue of their dependency from claim 1. However, Applicant reserves the right to further address the rejection of claims 2 and 11 in the future (Remarks, page 21).
Examiner respectively disagrees. As detailed in response to the arguments above, claim 1 is not allowable. Accordingly, claims 2 and 11 are not allowable.
Applicant further argues that claims 12, 14, and 20 include similar features as those of claims 1, 3, and 9, respectively, and as such are allowable for at least same reasons argued above (Remarks, page 21).
Examiner respectively disagrees. As detailed in response to the arguments above, claims 1, 3, and 9 are not allowable. Accordingly, claims 12, 14, and 20 are not allowable.
Applicant further argues that claims 13 and 18 depend from claim 12 and as such are allowable at least by virtue of their dependency from claim 12. However, Applicant reserves the right to further address the rejection of claims 13 and 18 in the future (Remarks, page 21).
Examiner respectively disagrees. As detailed in response to the arguments above, claim 12 is not allowable. Accordingly, claims 13 and 18 are not allowable.
Applicant further argues that claim 21 includes similar features as those of claim 1 and as such is allowable for at least same reasons argued above with respect to claim 1 (Remarks, page 21).
Examiner respectively disagrees. As detailed in response to the arguments above, claim 1 is not allowable. Accordingly, claim 21 is not allowable.
Applicant further argues that claims 4, 6-8, 10, 15, 17, and 19 stand rejected under 35 U.S.C. § 103 as being unpatentable over Gregov, in view of Pillarisetty, in further view of Subramanya et al. (US 2016/0063590 Al), hereinafter Subramanya. These claims depend directly or indirectly from either claim 1 or claim 12 and as such are allowable at least by virtue of their dependency from claim 1 or claim 12. However, Applicant reserves the right to further address the rejection of claims 4, 6-8, 10, 15, 17, and 19 in the future (Remarks, page 21).
Examiner respectively disagrees. As detailed in response to the arguments above, claims 1 and 12 are not allowable. Accordingly, claims 4, 6-8, 10, 15, 17, and 19 are not allowable.
Applicant further argues that claims 5 and 16 stand rejected under 35 U.S.C. § 103 as being unpatentable over Gregov, in view of Pillarisetty, in further view of Subramanya, in further view of Pyati et al. (US 2019/0311301 Al), hereinafter Pyati. These claims depend directly or indirectly from either claim 1 or claim 12 and as such are allowable at least by virtue of their dependency from claim 1 or claim 12. However, Applicant reserves the right to further address the rejection of claims 5 and 16 in the future (Remarks, page 21).
Examiner respectively disagrees. As detailed in response to the arguments above, claims 1 and 12 are not allowable. Accordingly, claims 5 and 16 are not allowable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
-Boteanu et al. (US 11,036,801 B1) teaches an interface that is dynamic and that provides selectable links in response to a query for products in an electronic marketplace.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ARIELLE E WEINER/ Primary Examiner, Art Unit 3689
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