DETAILED ACTION
This rejection is in response to Request for Continued Examination filed 06/06/2026.
Claims 1-20 are currently pending and have been examined.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/09/2026 has been entered.
Response to Arguments
Applicant’s arguments, see page 9, filed 06/09/2026, with respect to Claim Objection to claim 19 and 35 U.S.C. 112(b) rejection to claims 19-20 have been fully considered and are persuasive. The Claim Objection to claim 19 and 35 U.S.C. 112(b) rejection to claims 19-20 has been withdrawn.
Applicant's arguments filed 06/09/2026 have been fully considered but they are not persuasive.
With respect to Applicant’s arguments on pages 9-10 of remarks filed 06/09/2026 that the claims are not directed to certain methods of organizing human activity because the claim recites technical implementations for performing real-time inventory mapping using a hierarchical data structure that stores user associations, Examiner respectfully disagrees.
One of the enumerated groupings of abstract ideas is defined as certain methods of organizing human activity that includes fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). See MPEP § 2106.04(a)(2).
The claimed invention recites commercial interactions such as advertising, marketing, and sales activities by receiving behavioral data from a user indicating an interest in a category or in a seller, dynamically associating the user and the category or the user and the seller within a hierarchical data structure, and upon detecting a trigger, querying the hierarchical data structure, determining based on querying that an item associated with the category or the seller has been listed in an inventory, and transmitting instructions to display item data associated with the item in real-time. The storing of associations is not interpreted as directed to an abstract idea, but it is interpreted as an additional element.
With respect to Applicant’s arguments on pages 10-14 of remarks filed 06/09/2026 that the claims are directed to a practical application because it recites how the computer system performs the real-time mapping and notification, the claims improve computer functionality by associating users with interest by the hierarchical data structure and querying only relevant portions of the data structure, and Claim 12 also requires a saved search database storing the mappings which is directed to a specific improvement in database access and search engines, Examiner respectfully disagrees.
If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art. After the examiner has consulted the specification and determined that the disclosed invention improves technology, the claim must be evaluated to ensure the claim itself reflects the disclosed improvement in technology. An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. See MPEP § 2106.05(a).
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. See MPEP § 2106.05(f) and § 2106.05(a)(II).
It is unclear to one of ordinary skill in the art how dynamically associating users with interests, querying relevant portions of a data structure, and storing data in a saved search database improves computer functionality. Applicant’s specification paragraph [0015] states that better results are achieved compared to traditional search engines. Querying relevant portions of a data structure based on the mappings may provide better results which appears to solve a commercial problem rather than a problem rooted in technology. Therefore, 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.
With respect to Applicant’s arguments on pages 11-15 of remarks filed 06/09/2026 that the claim is meaningfully limited to a particular event driven search engine architecture, the claim recites an inventive concept because it requires specific limitations to solve technical problems, and the claims are not well-understood, routine, or conventional, Examiner respectfully disagrees.
In addition, a specific way of achieving a result is not a stand-alone consideration in Step 2A Prong Two. However, the specificity of the claim limitations is relevant to the evaluation of several considerations including the use of a particular machine, particular transformation and whether the limitations are mere instructions to apply an exception. See MPEP § 2106.04(d)(I).
The analysis of whether the claim includes other meaningful limitations may be relevant for both eligibility analysis Step 2A Prong Two, and Step 2B. The claim should add meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment to transform the judicial exception into patent-eligible subject matter. The phrase "meaningful limitations" has been used by the courts even before Alice and Mayo in various contexts to describe additional elements that provide an inventive concept to the claim as a whole. The considerations described in MPEP § 2106.05(a)-(d) are meaningful limitations when they amount to significantly more than the judicial exception, or when they integrate a judicial exception into a practical application. This broad label signals that there can be other considerations besides those described in MPEP § 2106.05(a)-(d) that when added to a judicial exception amount to meaningful limitations that can transform a claim into patent-eligible subject matter. See MPEP § 2106.05(e).
Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include: adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer. See MPEP § 2106.05(I)(A).
A specific way of achieving a result to provide search results using specific limitations or a particular event driven search engine is not a stand-alone consideration in Step 2A Prong Two.
The claims do not meaningfully limit the abstract idea because the additional elements (e.g. processor, storing data, and user device) merely link the use of the abstract idea to a particular technological environment. The limitations are not enough to qualify as significantly more because they merely invoke the computer as a tool to perform the abstract idea and do not improve computer capabilities. The claims are not interpreted as well-understood, routine, or conventional and do not invoke the Berkheimer Memo.
With respect to Applicant’s arguments on pages 16-19 of remarks filed 06/09/2026 that Harris does not teach a saving a search (e.g. Claim 1) or saved search database (e.g. Claim 12), Examiner respectfully disagrees.
Applicant’s arguments with respect to claim amendments (e.g. saving a search and saved search database) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
With respect to Applicant’s arguments on pages 17-18 of remarks filed 06/09/2026 that Harris does not teach querying the hierarchical data structure at one or more restricted levels, Examiner respectfully disagrees.
Harris teaches querying the hierarchical data structure at one or more restricted levels because this reference teaches searching a linking node mesh represented as a data structure that is indexed based on nodes for entities and edges that represent associations between nodes. The nodes that are searched may include meta-concepts related to the user based on aggregated transaction records (e.g. merchant and category) or concepts that are not linked yet. The structure of the linking node mesh that is indexed reduces hops from a given entity to any other entity within the indexed data structure which speeds up searches. (Harris, [0186]; [0320]; [0324]; [0316]; [0318]; FIG. 46B, [0327]; [0263]).
With respect to Applicant’s arguments on page 20 of remarks filed 06/09/2026 that claim 2-11, 13-18, and 20 further define novel features and depend on claims 1, 12, or 19 and the reference does not teach the dependent claims, Examiner respectfully disagrees.
Applicant's arguments do not comply with 37 CFR 1.111(c) because they do not clearly point out the patentable novelty which he or she thinks the claims present in view of the state of the art disclosed by the references cited or the objections made. Further, they do not show how the amendments avoid such references or objections.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (an abstract idea) without significantly more.
Under Step 1 of the Subject Matter Eligibility Test, it must be considered whether the claims are directed to one of the four statutory classes of invention. See MPEP § 2106. In the instant case, claims 1-11 are directed to a method, claims 12-18 is directed to one or more non-transitory computer storage media, and claims 19-20 are directed to a system ( which falls within one of the four statutory categories of invention (process/apparatus). Accordingly, the claims will be further analyzed under revised step 2:
Under step 2A (prong 1) of the Subject Matter Eligibility Test, it must be considered whether the claims recite a judicial exception if so, then determine in Prong Two if the recited judicial exception is integrated into a practical application of that exception. If the claim recites a judicial exception (i.e., an abstract idea), the claim requires further analysis in Prong Two. One of the enumerated groupings of abstract ideas is defined as certain methods of organizing human activity that includes fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). See MPEP § 2106.04(a)(2).
Regarding representative independent claim 1, recites the abstract idea of:
a method of providing real-time inventory mapping and notification, the method comprising:
receiving behavioral data from a user indicating an interest in a category or in a seller wherein the behavioral data corresponds to saving a search comprising one or more keywords that are associated with a category or following a seller;
dynamically associating the user and the category or the user and the seller within a hierarchical data structure, wherein the hierarchical data structure maintains a multi-level hierarchy of categories…;
upon detecting a configurable trigger, querying the hierarchical data structure at one or more restricted levels to determine users directly connected to a category and user indirectly connected through subcategories; and
determining, based on querying the hierarchical data structure, that an item associated with the category or the seller has been listed in an inventory transmitting instructions... to display item data associated with the item in real-time.
The above-recited limitations amounts to certain methods of organizing human activity as it relates to sales activities and commercial interactions because the claim recites receiving behavioral data from a user indicating an interest in a category or in a seller, dynamically associating the user and the category or the user and the seller within a hierarchical data structure, and upon detecting a trigger, querying the hierarchical data structure, determining based on querying that an item associated with the category or the seller has been listed in an inventory, and transmitting instructions to display item data associated with the item in real-time. Accordingly, the claim recites an abstract idea. See MPEP § 2106.
The Step 2A (prong 2) of the Subject Matter Eligibility Test, is the next step in the eligibility analyses and looks at whether the abstract idea is integrated into a practical application. This requires an additional element or combination of additional elements in the claims to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. See MPEP § 2106.
In this instance, the claims recite the additional elements such as:
…and stores associations between users and at least one level of the hierarchy …to a user device associated with the user… (Claim 1);
One or more non-transitory computer storage media storing computer-readable instructions that when executed by a processor, cause the processor to perform operations, the operations comprising: …stores a hierarchical data structure including a mapping between users and categories or users and sellers and wherein dynamically associating includes storing the association in a saved search database; … to a user device associated with the user… (Claim 12);
A system for providing real-time inventory mapping and notification: at least one processor; and one or more computer storage media storing computer-readable instructions that when executed by the at least one processor, cause the at least one processor to perform operations comprising:… stores associations between users and at least one level of the hierarchy;… to a user device associated with the user … (Claim 19).
However, these elements do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or 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, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Independent claims and dependent claims also fail to recite elements which amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or 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, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. For example, independent claims and dependent claims are directed to the abstract idea itself and do not amount to an integration according to any one of the considerations above.
Step 2B is the next step in the eligibility analyses and evaluates whether the claims recite additional elements that amount to an inventive concept (i.e., “significantly more”) than the recited judicial exception. According to Office procedure, revised Step 2A overlaps with Step 2B, and thus, many of the considerations need not be re-evaluated in Step 2B because the answer will be the same. See MPEP § 2106.
In Step 2A, several additional elements were identified as additional limitations:
…and stores associations between users and at least one level of the hierarchy …to a user device associated with the user… (Claim 1);
One or more non-transitory computer storage media storing computer-readable instructions that when executed by a processor, cause the processor to perform operations, the operations comprising: …stores a hierarchical data structure including a mapping between users and categories or users and sellers and wherein dynamically associating includes storing the association in a saved search database; … to a user device associated with the user… (Claim 12);
A system for providing real-time inventory mapping and notification: at least one processor; and one or more computer storage media storing computer-readable instructions that when executed by the at least one processor, cause the at least one processor to perform operations comprising:… stores associations between users and at least one level of the hierarchy;… to a user device associated with the user … (Claim 19).
These additional limitations, including the limitations in the independent claims and dependent claims, do not amount to an inventive concept because the recitations above do not amount to an improvement in the functioning of a computer or any other technology or technical field, apply the judicial exception with, or by use of, a particular machine, or 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, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. In addition, they were already analyzed under Step 2A and did not amount to a practical application of the abstract idea.
For these reasons, the claims are rejected under 35 U.S.C. 101.
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.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Harris et al. (US Pub. No. 20130290234 A1, hereinafter “Harris”) in view of Aubry et al. (U.S. Pub. No. 20130073586 A1).
Regarding claim 1
Harris discloses a method of providing real-time inventory mapping and notification, the method comprising (Harris, [0255]: provide real-time product suggestions to user):
receiving behavioral data from a user indicating an interest in a category or in a seller wherein the behavioral data corresponds to …comprising one or more keywords that are associated with a category or following a seller; (Harris, [0156]: obtain various human behavioral information; [0263]: user behavioral patterns based on aggregated records such as merchant name or category; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and categories);
dynamically associating the user and the category or the user and the seller within a hierarchical data structure, wherein the hierarchical data structure maintains a multi-level hierarchy of categories and stores associations between users and at least one level of the hierarchy; (Harris, [0316]: linking node mesh may be represented as a modified graph data structure that contains nodes for entities and edges that represent the associations between the nodes that are actual observable entities, such as a user 4401 and a business 4403 as well as aggregated transaction data; FIG. 46B, [0327]: linking node mesh is indexed; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and for particular products types, and categories; [0183]: store each object (e.g., user, merchant, issuer, acquirer, IP address, household, etc.) as a node; [0263]: user behavioral patterns based on aggregated records such as merchant name or category);
upon detecting a configurable trigger, querying the hierarchical data structure at one or more restricted levels to determine users directly connected to a category and user indirectly connected through subcategories (Harris, [0186]: updating of profile and/or social graphs for an entity may trigger a search for additional data that may be relevant; [0320]: the link nodes may contain information about the nodes that they connect to. In so doing, the number of nodes in the graph that need to be searched in order to find a given type, magnitude or value of connection may be reduced logarithmically and the edges themselves may have metadata (e.g. connection between nodes) associated with them that enable faster or better querying of the mesh; [0324]: linking node mesh search; [0316]: deduced entity nodes including a deduced item (e.g. user’s family member’s items) inserted into the graph mesh that determines a concept that is not yet linked into the mesh graph; [0318]: meta-concepts are conceptual nodes that are not defining a user (e.g. deduced item) but indicate an abstract concept that many more nodes may relate; [0319]: meta concepts, e.g., 4415, may be further linked to actual items; FIG. 46B, [0327]: linking node mesh is indexed to reduce the number of hops in the graph from a given entity to any other entity within the indexed graph, so as to advantageously speed searching of the graph; [0263]: user behavioral patterns based on aggregated records such as merchant name or category); and
determining, based on querying the hierarchical data structure, that an item associated with the category or the seller has been listed in an inventory transmitting instructions to a user device associated with the user to display item data associated with the item in real-time (Harris, [0351]: querying a linking node mesh; [0320]: querying nodes in the mesh graph; [0255]: mining user transaction records for behavioral and consumption patterns of products for preferences based on particular merchant and/or product categories, determines that products of interest to the user are available to provide product suggestions and offers to user in real-time in response to user behavior with product; [0261]: generate a real-time product offer packet and client may render display of purchase offer with item data to user; [0393]: merchant’s available inventory; [0349]: the user may be presented with a structured query interface on their mobile device that allows a restricted set of options; FIG. 46B, [0327]: linking node mesh is indexed; [0263]: user behavioral patterns based on aggregated records such as merchant name or category).
Harris does not teach:
saving a search…;
However, Aubry teaches:
saving a search…(Aubry, [0030]: database query results corresponding to expected queries are generally pre-computed and stored in a memory for allowing fast access to the pre-computed database query results; [0031]: The search platform 3 is arranged to process these queries on the basis of the stored pre-computed data and to return respective query results to the clients. Pre-computation of the database query results is performed by the computation platform 2 in response to pre-computation requests generated by search platform; [0150] The databases 301; [0356]: database in memory).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the behavioral data of Harris with saving a search as taught by Aubry because the results of such a modification would be predictable. Specifically, Harris would continue to teach the behavioral data except that now saving a search is taught according to the teachings of Aubry in order to provide faster queries. This is a predictable result of the combination. (Aubry, [0032]).
Regarding claims 2 and 13
The combination of Harris and Aubry teaches the method of claim 1, wherein the hierarchical data structure and restricted-level querying are configured such that … (Harris, [0186]: updating of profile and/or social graphs for an entity may trigger a search for additional data that may be relevant to the newly identified correlations and associations for each entity, e.g., via search term generation component(s); [0320]: the link nodes may contain information about the nodes that they connect to. In so doing, the number of nodes in the graph that need to be searched in order to find a given type, magnitude or value of connection may be reduced logarithmically and the edges themselves may have metadata (e.g. connection between nodes) associated with them that enable faster or better querying of the mesh; [0324]: linking node mesh search; [0316]: deduced entity nodes including a deduced item (e.g. user’s family member’s items) inserted into the graph mesh that determines a concept that is not yet linked into the mesh graph; [0318]: meta-concepts are conceptual nodes that are not defining a user (e.g. deduced item) but indicate an abstract concept that many more nodes may relate; [0319]: meta concepts, e.g., 4415, may be further linked to actual items; FIG. 46B, [0327]: linking node mesh is indexed).
Harris does not teach:
issuing the notification does not require executing a batch scan of all saved searches and instead limits queries to a smaller portion of the database.
However, Aubry teaches:
issuing the notification does not require executing a batch scan of all saved searches and instead limits queries to a smaller portion of the database (Aubry, [0049]: analyze and decompose the batch re-computation order into smaller computation packages relating to a subset of the plurality of database query results. Hence, the actual computation is performed on the level of the smaller computation packages as opposed to the overall batch re-computation order; [0030]: database query results corresponding to expected queries are generally pre-computed and stored in a memory for allowing fast access to the pre-computed database query results).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the querying of Harris with issuing the notification does not require executing a batch scan of all saved searches and instead limits queries to a smaller portion of the database as taught by Aubry because the results of such a modification would be predictable. Specifically, Harris would continue to teach querying except that now issuing the notification does not require executing a batch scan of all saved searches and instead limits queries to a smaller portion of the database is taught according to the teachings of Aubry in order to effectively handle high volume of data. This is a predictable result of the combination. (Aubry, [0005]).
Regarding claims 3 and 14
The combination of Harris and Aubry teaches the method of claim 2, further comprising dynamically disassociating the user and the category or the user and the seller within the data structure (Harris, [0316]: data structure that contains nodes for entities and edges that represent the associations between the nodes that are actual observable entities, such as a user 4401 and a business 4403 as well as aggregated transaction data; [0327]: nodes are sequentially removed; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and for particular products types, and categories; [0183]: store each object (e.g., user, merchant, issuer, acquirer, IP address, household, etc.) as a node).
Regarding claim 4
The combination of Harris and Aubry teaches the method of claim 1, further comprising, based on detecting that the item associated with the category or seller has been listed in an inventory, retrieving the item data corresponding to an association between the user and the category or the user and the seller (Harris, [0255]: mine user patterns from records, indicate product category and merchant preference of user, and provide product suggestions to user in real-time in response to user behavior and preferences (e.g. category and merchant) with product based on records).
Regarding claims 5 and 17
The combination of Harris and Aubry teaches the method of claim 1, wherein the data structure is a graph database (Harris, [0183]: graph database; [0450]: database may be implemented as a mix of data structures).
Regarding claims 6 and 15
The combination of Harris and Aubry teaches the method of claim 1, wherein the behavioral data corresponds to the user saving a search comprising one or more keywords (Harris, [0377]: search for product based on tone of keywords identified; [0190]: parse the trigger to extract keywords using which to perform an aggregated search; [0188]: query, e.g., 1017a-c, their search databases, e.g., 1002a-c, for search results falling within the scope of the search keywords; [0144]: store records of search request with key terms to be used on a second search).
Regarding claims 7 and 16
The combination of Harris and Aubry teaches the method of claim 1, wherein the behavioral data corresponds to the user following the seller (Harris, [0159]: consumer obtains offers from merchant or browses merchant store; [0191]: user may communicate with a merchant server).
Regarding claim 8
The combination of Harris and Aubry teaches the method of claim 1, wherein detecting that the item associated with the category has been listed in an inventory is a configurable trigger (Harris, [0255]: provide available products as suggestions or offers to user in real-time in response to mining records of user behavior that indicates preferences (e.g. category and merchant) with product; [0361]: aggregate consumer behavior, divided based on product category).
Regarding claim 9
The combination of Harris and Aubry teaches the method of claim 1, wherein detecting that the item associated with the seller has been listed in an inventory is a configurable trigger (Harris, FIG. 30: [0262]: identify, e.g., 3005, merchants that may be able to provide the identified products, services, and/or offerings for the user; Harris, [0255]: provide available product suggestions or offers to user in real-time in response data mining records of user behavior to indicate preferences (e.g. category and merchant) with product; [0393]: inventory).
Regarding claim 10
The combination of Harris and Aubry teaches the method of claim 1, further comprising detecting an incentive being provided for the item or by the seller (Harris, FIG. 30: [0262]: identify, e.g., 3005, merchants that may be able to provide the identified products, services, and/or offerings for the user; Harris, [0255]: provide product suggestions of deals and offerings to user in real-time in response to user behavior and preferences (e.g. category and merchant) with product).
Regarding claim 11
The combination of Harris and Aubry teaches the method of claim 1, further comprising identifying the item as a fit for another associated with the user (Harris, [0377]: determine suitable alternative product for the user as a replacement item for another item).
Regarding claim 12
Harris discloses one or more non-transitory computer storage media storing computer-readable instructions that when executed by a processor, cause the processor to perform operations, the operations comprising (Harris, [0969]: non-transitory medium and processor):
receiving behavioral data from a user indicating an interest in a category or in a seller wherein the behavioral data corresponds to … comprising one or more keywords that are associated with a category or a seller (Harris, [0156]: obtain various human behavioral information; [0263]: user behavioral patterns based on aggregated records such as merchant name or category; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and for particular products types, and categories);
dynamically associating the user and the category or the user and the seller in a data structure wherein the data structure comprises a…database that stores a hierarchical data structure including a mapping between users and categories or users and sellers and wherein dynamically associating includes storing the association in a … database (Harris, [0316]: linking node mesh may be represented as a modified graph data structure that contains nodes for entities and edges that represent the associations between the nodes that are actual observable entities, such as a user 4401 and a business 4403 as well as aggregated transaction data; FIG. 46B, [0327]: linking node mesh is indexed; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and for particular products types, and categories; [0183]: store each object (e.g., user, merchant, issuer, acquirer, IP address, household, etc.); [0263]: user behavioral patterns based on aggregated records such as merchant name or category; [0321]: the distributed linking node mesh may be stored in a database);
upon detecting that an item associated with the category or the seller has been listed in an inventory, querying only a relevant portion of the hierarchical data structure, the relevant portion being the portion of the hierarchical data structure associated with the category or seller to retrieve item data for an item corresponding to an association between the user and the category or the user and the seller; and transmitting instructions to a user device associated with the user to display the item data in real-time (Harris, [0351]: querying a linking node mesh; [0320]: querying nodes in the mesh graph; [0327]: index may form a graph that to search; [0255]: mining user transaction records for behavioral and consumption patterns of products for preferences based on particular merchant and/or product categories, determines that products of interest to the user are available to provide product suggestions and offers to user in real-time in response to user behavior with product; [0261]: generate a real-time product offer packet and client may render display of purchase offer with item data to user; [0393]: merchant’s available inventory; [0349]: the user may be presented with a structured query interface on their mobile device that allows a restricted set of options; FIG. 46B, [0327]: linking node mesh is indexed; [0266]: filter data records to include only those records as relevant to the analysis; [0186]: trigger a search for additional data that may be relevant; [0263]: user behavioral patterns based on aggregated records such as merchant name or category).
Harris does not teach:
saving a search…;
a saved search database...;…a saved search database…
However, Aubry teaches:
saving a search…; a saved search database...;…a saved search database…(Aubry, [0030]: database query results corresponding to expected queries are generally pre-computed and stored in a memory for allowing fast access to the pre-computed database query results; [0031]: Database system and search platform 3 is arranged to process these queries on the basis of the stored pre-computed data and to return respective query results to the clients. Pre-computation of the database query results is performed by the computation platform 2 in response to pre-computation requests generated by search platform; [0150] The databases 301; [0356]: database in memory).
The motivation to combine Harris and Aubry is the same as set forth above in claim 1.
Regarding claims 18 and 20
The combination of Harris and Aubry teaches the one or more non-transitory computer storage media of claim 12, wherein the operations further comprise detecting an incentive being provided for the item or by the seller (Harris, FIG. 30: [0262]: identify, e.g., 3005, merchants that may be able to provide the identified products, services, and/or offerings for the user; [0255]: provide product suggestions of deals and offerings to user in real-time in response to user behavior and preferences (e.g. category and merchant) with product; [0377]: determine suitable alternative product for the user as a replacement item for another item; [0393]: inventory).
Regarding claim 19
Harris discloses a system for providing real-time inventory mapping and notification: at least one processor; and one or more computer storage media storing computer-readable instructions that when executed by the at least one processor, cause the at least one processor to perform operations comprising (Harris, [0418]: computer employing processor and memory storage, [1167]: memory in communication with processor; [0393]: merchant’s available inventory):
receiving behavioral data from a user indicating an interest in a category or in a seller wherein the behavioral data corresponds to … comprising one or more keywords that are associated with a category or following a seller; (Harris, [0156]: obtain various human behavioral information; [0263]: user behavioral patterns based on aggregated records such as merchant name or category; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and for particular products types, and categories);
dynamically associating the user with the interest in a data structure wherein the hierarchical data structure maintains a multi-level hierarchy of categories and stores associations between users and at least one level of the hierarchy (Harris, [0316]: linking node mesh may be represented as a modified graph data structure that contains nodes for entities and edges that represent the associations between the nodes that are actual observable entities, such as a user 4401 and a business 4403 as well as aggregated transaction data; FIG. 46B, [0327]: linking node mesh is indexed; [0255]: analysis of the aggregated user card transaction records may indicate a preference for shopping with particular merchants and for particular products types, and categories; [0183]: store each object (e.g., user, merchant, issuer, acquirer, IP address, household, etc.) as a node);
upon detecting a configurable trigger, querying only a relevant portion of the hierarchical data structure associated with the category or seller (Harris, [0186]: updating of profile and/or social graphs for an entity may trigger a search for additional data that may be relevant; [0320]: the link nodes may contain information about the nodes that they connect to. In so doing, the number of nodes in the graph that need to be searched in order to find a given type, magnitude or value of connection may be reduced logarithmically and the edges themselves may have metadata (e.g. connection between nodes) associated with them that enable faster or better querying of the mesh; [0324]: linking node mesh search; [0316]: the linking node mesh may be represented as a modified graph data structure; [0318]: meta-concepts are conceptual nodes; [0319]: meta concepts, e.g., 4415, may be further linked to actual items; FIG. 46B, [0327]: linking node mesh is indexed to reduce the number of hops in the graph from a given entity to any other entity within the indexed graph, so as to advantageously speed searching of the graph; [0263]: user behavioral patterns based on aggregated records such as merchant name or category; [0266]: filter data records to include only those records as relevant to the analysis; [0186]: trigger a search for additional data that may be relevant);
determining, based on querying only the relevant portion of the hierarchical data structure, that that an item associated with the category or the seller has been listed in an inventory, retrieving item data for an item corresponding to an item in an inventory of items; and transmitting instructions to a user device associated with the user in real-time (Harris, [0351]: querying a linking node mesh; [0320]: querying nodes in the mesh graph; [0327]: index may form a graph that to search; [0255]: mining user transaction records for behavioral and consumption patterns of products for preferences based on particular merchant and/or product categories, determines that products of interest to the user are available to provide product suggestions and offers to user in real-time in response to user behavior with product; [0261]: generate a real-time product offer packet and client may render display of purchase offer with item data to user; [0393]: merchant’s available inventory; [0349]: the user may be presented with a structured query interface on their mobile device that allows a restricted set of options; FIG. 46B, [0327]: linking node mesh is indexed; [0263]: user behavioral patterns based on aggregated records such as merchant name or category).
Harris does not teach:
saving a search…;
However, Aubry teaches:
saving a search… (Aubry, [0030]: database query results corresponding to expected queries are generally pre-computed and stored in a memory for allowing fast access to the pre-computed database query results; [0031]: Database system and search platform 3 is arranged to process these queries on the basis of the stored pre-computed data and to return respective query results to the clients. Pre-computation of the database query results is performed by the computation platform 2 in response to pre-computation requests generated by search platform; [0150] The databases 301; [0356]: database in memory).
The motivation to combine Harris and Aubry is the same as set forth above in claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is cited as Henderson et al. (US Pub. No. 20220292543 A1) is related to providing e-commerce involving social media and detected trends or seasonal demands, Rathod (US Pub. No. 20180246983 A1) related to providing of a ‘web search engine’ that is designed to search for information, and non-patent literature, "Post-purchase recommendations in large-scale online marketplaces," related to recommendations shopping websites present to the users after a purchase based on learned relationships between items and users.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LATASHA DEVI RAMPHAL whose telephone number is (571)272-2644. The examiner can normally be reached 11 AM - 7:30 PM (EST).
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/LATASHA D RAMPHAL/Examiner, Art Unit 3688
/KELLY S. CAMPEN/Primary Examiner, Art Unit 3691
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