DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10/30/2025 has been entered.
Status of Claims
Applicant’s communications filed on 10/30/2025 have been considered.
Claims 1 and 9-16 have been amended.
Claims 1-16 are currently pending and have been examined.
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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an abstract idea. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
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. Claims 1-8 are directed towards a process. Claims 9-16 are directed towards a system. Therefore, claims 1-16 are directed to one of the four statutory categories (YES).
Under Step 2A of the MPEP, 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. In determining whether the claims are directed to a judicial exception, the claims are analyzed to evaluate whether the claims recite a judicial exception.
Taking Claim 9 as representative, claim 9 recites limitations that fall within the certain methods of organizing human activity groupings of abstract ideas, including:
capture, via a user, a first item identifier of a first item retrieved by the user from a tag affixed to the first item;
determine an item set containing a captured item identifier and a confidence level associated with the item set;
determine whether the first item identifier matches one of a plurality of primary item identifiers;
in response to determining that the first item identifier matches one of the primary item identifiers, provide input data to a model, the input data including the first item identifier;
determine, via execution of the model, an item set identifier corresponding to an item set containing the first item identifier, the item set being indicative of one or more items associated with the first item; and
present the item set identifier.
Claim 1 recites the same limitations believed to be abstract as recited in claim 9.
Claim 9, as exemplary, recites the abstract idea of recommending item sets. These recited limitations fall within the "Certain Methods of Organizing Human Activities" Grouping of abstract ideas as it relates to commercial interactions of sales activities or behaviors. Accordingly, the claim recites an abstract idea. See MPEP 2106.04.
Furthermore, the claims recite determin[ing] whether the first item identifier matches one of a plurality of primary item identifiers, which further falls under the Mental Processes subgrouping, as it relates to concept performed in the human mind, including evaluation and judgment.
Accordingly, under Prong One of Step 2A of the Alice/Mayo test, claims 1 and 9 recite an abstract idea (Step 2A, Prong One: YES).
Under Prong 2, it is determined whether the claim recites additional elements that integrate the exception into a practical application of the exception.
Claim 9 recites additional elements beyond the judicial exception(s), including A computing device, comprising: a radio frequency identification (RFID) reader; a display; and a processor configured to: capture, via the RFID reader of the mobile computing device, an RFID tag; and train a classification model via a plurality of input data sets including one or more item identifiers. Claim 1 recites the same additional elements as recited in claim 9.
These additional elements are described at a high level in Applicant’s specification without any meaningful detail about their structure or configuration. As such, these computer-related limitations are not found to be sufficient to integrate the abstract idea into a practical application. Claims 1 and 9 specifying that the abstract idea of recommending item sets is executed in a computer environment merely indicates a field of use in which to apply the abstract idea because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer. As such, under Prong Two of Step 2A of the Alice/Mayo test, when considered both individually and as a whole, the limitations of claims 1 and 9 are not indicative of integration into a practical application (Step 2A, Prong Two: NO).
Since claims 1 and 9 recite an abstract idea and fail to integrate the abstract idea into a practical application, claims 1 and 9 are “directed to” an abstract idea (Step 2A: YES). Accordingly, the judicial exception is not integrated into a practical application.
Next, under Step 2B, the instant claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, the additional elements of A computing device, comprising: a radio frequency identification (RFID) reader; a display; and a processor configured to: capture, via the RFID reader of the mobile computing device, an RFID tag; and train a classification model via a plurality of input data sets including one or more item identifiers amount to no more than mere instructions to apply the exception using generic computer components. For the same reason these elements are not sufficient to provide an inventive concept. Therefore when considering the additional elements alone, and in combination, there is no inventive concept in the claim, and thus the claim is not patent eligible (Step 2B: NO).
Dependent claims 2-8 and 10-16, 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. As for dependent claims 3-4, 6-8, 11, 12, and 14-16, these claims recite limitations that further define the same abstract idea noted in independent claims 1 and 9. Therefore, claims 3-4, 6-8, 11, 12, and 14-16 are considered patent ineligible for the reasons given above.
As for dependent claims 2, 5, 10 and 13, these claims recite limitations that further define the abstract idea noted in independent claims 1 and 9. Additionally, they recite the following additional limitations:
storing, in a memory of the mobile computing device, a list of the primary item identifiers;
in response to presenting the item set identifier at the output, receiving a selection of the item set identifier via an input of the mobile computing device;
The additional elements of a memory of the mobile computing device and an input of the mobile computing device are all recited at a high level of generality such that they amount to no more than instructions to apply the judicial exception in a generic technological environment. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. Accordingly, under the Alice/Mayo test, claims 1-16 are ineligible.
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.
Claims 1-2, 6-10 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited Ahuja (US 2024/0144173 A1) in view of newly cited U.S Patent Application No. 2020/0273013 to Garner, hereinafter Garner.
Regarding Claim 1, Ahuja discloses A method, comprising ([0075]):
capturing, via a radio frequency identification (RFID) reader of a mobile computing device associated with a user, a first item identifier of a first item retrieved by the user from an RFID tag affixed to the first item ([0011] The customer client device 100 can be a personal or mobile computing device; [0016] the customer client device 100 may include various components (e.g., cameras, barcode readers, RFID scanners, sensors, etc.) that the customer client device 100 uses to capture various types of data associated with items in the food storage area, including RFID tags included on packaging for the items; [0060] once the item detection module 250 receives data associated with the contents of the food storage area captured by the customer client device 100, the item detection module 250 compares the data received from the customer client device 100 to item data stored in the data store 240; [0078-0079] the online concierge system 140 may also detect 305 the acquired item 405 if the packaging for the item 405 includes an RFID tag that transmits data (e.g., a SKU) to the customer client device… see [0055] the catalog of items may include… an item identifier associated with each item);
operating a classification model via a plurality of input data sets including one or more item identifiers to determine an item set containing a captured item identifier and a confidence level associated with the item set ([0070] The recipe scoring module 270 retrieves a set of attributes associated with a customer and a set of recipes that the recipe matching module 265 matches with one or more candidate available items to the customer; [0072] The recipe scoring module 270 also computes a suggestion score for each recipe included among the set of recipes that the recipe matching module 265 matches with the one or more candidate available items to the customer… the suggestion score may account for various factors, such as a likelihood that the customer will have an affinity for the recipe… see [0016][0060-0063] the customer may capture identifiers of candidate available items via the customer’s client device 100) (Examiner notes that a confidence level has been interpreted as a score indicating the likelihood that the customer will select a particular item set, per Applicant’s specification ([0045]));
determining whether the first item identifier matches one of a plurality of primary item identifiers ([0068] The recipe matching module 265 retrieves recipes (e.g., from the recipe store 260) and matches one or more candidate available items to a customer with a set of the recipes. The recipe matching module 265 may do so based on one or more ingredients of each recipe and the one or more candidate available items to the customer) (Examiner notes that the one or more ingredients of each recipe that is matched to the customer’s available items have been interpreted as a plurality of item identifiers);
in response to determining that the first item identifier matches one of the primary item identifiers, providing input data to a classification model, the input data including the first item identifier ([0070] The recipe scoring module 270 retrieves… a set of recipes that the recipe matching module 265 matches with one or more candidate available items to the customer… The set of attributes retrieved by the recipe scoring module 270 also may include ingredients of each recipe that the recipe matching module 265 matches with the one or more candidate available items to the customer; [0071] the set of recipes retrieved by the recipe scoring module 270 also may include an expected value associated with a set of remaining items for each of the set of recipes. The expected value associated with the set of remaining items for a recipe may be based on a probability that the customer will acquire each remaining item and a value associated with each remaining item);
determining, via execution of the classification model, an item set identifier corresponding to an item set containing the first item identifier, the item set being indicative of one or more items associated with the first item ([0072] The recipe scoring module 270 also computes a suggestion score for each recipe included among the set of recipes that the recipe matching module 265 matches with the one or more candidate available items to the customer… The suggestion score for a recipe may account for… the expected value associated with the set of remaining items for the recipe; [0074] The recipe selection module 280 may select one or more recipes for suggesting to a customer from a set of recipes that the recipe matching module 265 matches with one or more candidate available items to the customer… once the recipe ranking module 275 has ranked the set of recipes, the recipe selection module 280 may select one or more recipes for suggesting to the customer based on the ranking); and
presenting the item set identifier at an output of the mobile computing device ([0093] The online concierge system 140 then sends 350 (e.g., using the content presentation module 210) the one or more recipes 500 selected 345 by the online concierge system 140 and a set of remaining items 405 identified 325 for each recipe 500 to the customer client device 100 associated with the customer… each recipe 500 may be presented in association with the set of remaining items 405 identified 325 for the recipe 500);
But does not explicitly disclose training a classification model; making a determination at the mobile computing device; and executing the trained classification model.
Garner, on the other hand, discloses training a classification model ([0042] the decision control circuit causes each frame of the subset of frames to be locally processed by at least one and typically a plurality of, if not all of, the multiple different trained machine learning modeling applications 320a-d. Typically, the subset of frames are locally processed on the portable device through the multiple different machine learning modeling applications 320a-d that are maintained on the memory 204 of the portable device and run locally on the portable device… a first trained, machine learning modeling application 320a can be configured to perform an object classification relative to one or more object classification attributes of a product captured within the subset of frames; [0076] the model training system can train models to be used local on customer portable user devices 102);
making a determination at the mobile computing device ([0042] the subset of frames are locally processed on the portable device through the multiple different machine learning modeling applications 320a-d that are maintained on the memory 204 of the portable device and run locally on the portable device; [0076] the model training system can train models to be used local on customer portable user devices 102); and
executing the trained classification model ([0045] The modeling applications respectively further include the trained, deep learning models 322a-c that processes the input data (e.g., the converted frame data of the frames of the subset of frames, and the converted known product data) to determine whether one or more of the frames of the subset of frames includes an image of a product, label of a product, or other portion of a product that at least partially corresponds with a known product… the object classification modeling applies a series of filters to narrow the potential items).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system, as taught by Ahuja, training a classification model; making a determination at the mobile computing device; and executing the trained classification model, as taught by Garner, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. It further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kim and Romani, to include the teachings of Piana, in order to provide local device processing for improving the ability to perform object identification of items such as retail products (Garner, [0003][0024]).
Regarding Claim 2, Ahuja and Garner teach the limitations of claim 1.
Ahuja further discloses storing, in a memory, a list of the primary item identifiers ([0066] The recipe store 260 includes information identifying recipes obtained by the online concierge system 140… each recipe may have one or more attributes describing the recipe. Examples of attributes of a recipe include ingredients of the recipe);
wherein determining whether the first item identifier matches one of a plurality of primary item identifiers includes determining whether the list includes the first item identifier ([0068] The recipe matching module 265 retrieves recipes (e.g., from the recipe store 260) and matches one or more candidate available items to a customer with a set of the recipes. The recipe matching module 265 may do so based on one or more ingredients of each recipe and the one or more candidate available items to the customer);
But does not explicitly disclose storing, in a memory of the mobile computing device, a list of primary item identifiers.
Garner, on the other hand, discloses storing, in a memory of the mobile computing device, a list of primary item identifiers ([0032] portable user device 102 includes memory 204… the memory stores one or more databases, including a local product database locally storing sets of product imaging data, where each set of product imaging data corresponds to different retail products available for sale from a retail store and includes a product identifier).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system, as taught by Ahuja, storing, in a memory of the mobile computing device, a list of primary item identifiers, as taught by Garner, for the same reasons discussed above with respect to claim 1.
Regarding Claim 6, Ahuja and Garner teach the limitations of claim 1.
Ahuja further discloses wherein obtaining the item set identifier includes obtaining a plurality of item set identifiers corresponding to distinct item sets each including the first item identifier ([0068] The recipe matching module 265 retrieves recipes (e.g., from the recipe store 260) and matches one or more candidate available items to a customer with a set of the recipes. The recipe matching module 265 may do so based on one or more ingredients of each recipe and the one or more candidate available items to the customer… the recipe matching module 265 may match the one or more candidate available items to the customer with the set of recipes based on the quantity of each ingredient required for each recipe).
Regarding Claim 7, Ahuja and Garner teach the limitations of claim 6.
Ahuja further discloses presenting the plurality of item set identifiers at the output ([0093] The online concierge system 140 then sends 350 (e.g., using the content presentation module 210) the one or more recipes 500 selected 345 by the online concierge system 140 and a set of remaining items 405 identified 325 for each recipe 500 to the customer client device 100 associated with the customer… each recipe 500 may be presented in association with the set of remaining items 405 identified 325 for the recipe 500).
Regarding Claim 8, Ahuja and Garner teach the limitations of claim 6.
Ahuja further discloses for each of the plurality of item set identifiers, querying an inventory repository to determine an availability of a set of items included in the item set ([0057] The item detection module 250 may detect a set of acquired items associated with a customer of the online concierge system 140, in which the set of acquired items is included among an inventory of the customer; [0063] The item availability module 255 identifies one or more candidate available items to a customer from a set of acquired items associated with the customer detected by the item detection module 250; [0068] the recipe matching module 265 may match the one or more candidate available items to the customer with the set of recipes based on the quantity of each ingredient required for each recipe and the quantity of each of the one or more candidate available items to the customer); and
when one or more of the set of items is unavailable, discarding the item set identifier without presenting the item set identifier at the output ([0068] suppose that only one 14-ounce can of tomatoes is included among the items identified by the item availability module 255 likely to be available to the customer and a recipe calls for 28 ounces of canned tomatoes. In this example, if none of the other ingredients of the recipe are included among the candidate available items to the customer, the recipe matching module 265 may not match the candidate available items to the customer with this recipe).
Claim 9 is directed to a computing device. Claim 9 recites limitations that are substantially parallel in nature to those addressed above for claim 1 which is directed towards a system. The method of Ahuja/Garner teaches the limitations of claim 1 as noted above. Ahuja further discloses A computing device, comprising: a sensor; a display; and a processor configured to: (Ahuja: [0011][0013][0095]). Claim 9 is therefore rejected for the reasons set forth above in claim 1 and in this paragraph.
Claim 10 recites a computing device comprising substantially similar limitations as claim 2. The claim is rejected under substantially similar grounds as claim 2.
Claim 14 recites a computing device comprising substantially similar limitations as claim 6. The claim is rejected under substantially similar grounds as claim 6.
Claim 15 recites a computing device comprising substantially similar limitations as claim 7. The claim is rejected under substantially similar grounds as claim 7.
Claim 16 recites a computing device comprising substantially similar limitations as claim 8. The claim is rejected under substantially similar grounds as claim 8.
Claims 3, 4, 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Ahuja in view of Garner, and further in view of previously cited Charles (US 2018/0096411 A1).
Regarding Claim 3, Ahuja and Garner teach the limitations of claim 1.
Ahuja further discloses prior to providing the classification model with the input data: capturing, via the sensor, at least one additional item identifier ([0016] the customer client device 100 may include various components (e.g., cameras, barcode readers, RFID scanners, sensors, etc.) that the customer client device 100 uses to capture various types of data associated with items in the food storage area; [0060] In some embodiments, once the item detection module 250 receives data associated with the contents of the food storage area captured by the customer client device 100, the item detection module 250 may detect the set of acquired items by accessing the data store 240 and comparing the data received from the customer client device 100 to item data stored in the data store 240);
But does not explicitly disclose in response to determining that the first item identifier matches one of the primary item identifiers, capturing at least one additional item identifier.
Charles, on the other hand, discloses a similar method for providing item sets to customers ([0022]), and additionally discloses in response to determining that the first item identifier matches one of the primary item identifiers, capturing at least one additional item identifier ([0054] The customer's Mobile device 190 has software which allows scanner 191 to read optical patterns, such as barcodes, or QR codes of packaging of ingredients in the store; [0057] In step 219 it is determined if the ingredient is part of a recipe. If so, (“yes”), then the customer is notified and the ingredient is stored; [0059] In step 225, if the customer 5 is purchasing most of the ingredients of a recipe, but not all of the ingredients, coupon redemption device 150 notifies POS device 140 to indicate such to the customer… indicating that the customer is close to fulfilling a complete recipe and indicates which ingredients are required to complete the recipe; [0061] If the customer 5 wants to suspend the checkout transaction (‘yes’), then it is suspended for a predetermined period of time to allow the customer 5 to go back into the store to get the missing ingredients and returns to the POS device 140).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system, as taught by Ahuja and Garner, in response to determining that the first item identifier matches one of the primary item identifiers, capturing at least one additional item identifier, as taught by Charles, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. It further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Ahuja and Beniwal, to include the teachings of Charles, in order to allow users to search recipes based upon cost levels and ingredient availability (Charles, [0009]).
Regarding Claim 4, Ahuja, Garner and Charles teach the limitations of claim 3.
Ahuja further discloses prior to providing the classification model with the input data: determining that a count of the first item identifier and the at least one additional item identifier exceeds a threshold ([0068] the recipe matching module 265 may match the one or more candidate available items to the customer with a recipe if at least a threshold number or percentage of the ingredients of the recipe correspond to the one or more candidate available items to the customer).
Claim 11 recites a computing device comprising substantially similar limitations as claim 3. The claim is rejected under substantially similar grounds as claim 3.
Claim 12 recites a computing device comprising substantially similar limitations as claim 4. The claim is rejected under substantially similar grounds as claim 4.
Claims 5 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Ahuja in view of Garner, and further in view of previously cited Chang (US 2014/0096479 A1).
Regarding Claim 5, Ahuja and Garner teach the limitations of claim 1.
Ahuja further discloses retrieving an item set definition corresponding to the item set identifier, the item set definition including at least a second item identifier ([0087] the online concierge system 140 also identifies… a set of remaining items 405 for each recipe 500 it matches 320 with the one or more items 405 likely to be available to the customer, in which each remaining item 405 corresponds to an ingredient of a recipe 500 that is not included among the one or more items 405 likely to be available to the customer); and
adding the second item identifier to a list of target items at the mobile computing device ([0093] The online concierge system 140 then sends… the one or more recipes 500 selected 345 by the online concierge system 140 and a set of remaining items 405 identified 325 for each recipe 500 to the customer client device 100 associated with the customer… each recipe 500 may be presented in association with the set of remaining items 405 identified 325 for the recipe 500);
But does not explicitly disclose in response to presenting the item set identifier at the output, receiving a selection of the item set identifier via an input of the mobile computing device.
Chang, on the other hand, discloses in response to presenting the item set identifier at the output, receiving a selection of the item set identifier via an input of the mobile computing device ([0044] In block 808, the mobile computing device 102 displays the selected recipes for the user. In some embodiments, the mobile computing device 102 will display the recipe recommendation based on the ingredient(s) available on hand; [0045] in block 812, the mobile computing device 102 determines whether the user has selected a recipe from the list of recipe recommendations; [0046] If a recipe has been selected by the user in block 812, the method 800 advances to block 816 in which the mobile computing device 102 may provide complementary recipes and/or suggestions to supplement the selected recipe).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the system, as taught by Ahuja and Garner, in response to presenting the item set identifier at the output, receiving a selection of the item set identifier via an input of the mobile computing device, as taught by Chang, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. It further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Ahuja and Beniwal, to include the teachings of Chang, in order to allow to provide recipe recommendations while allowing for future meal planning and monitoring the shelf life of ingredients for spoilage concerns (Chang, [0017][0021]).
Response to Arguments
Applicant’s arguments filed with respect to the rejection of claims under 35 USC 101 have been fully considered but they are not persuasive.
Applicant argues that the amended claims integrate the abstract idea into a practical application because “the claims provide that… information and data processing systems, and their related various components, may be improved or enhanced by providing accurate and efficient estimations” (Remarks Page 8). Examiner respectfully disagrees. The specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. MPEP 2106.04(d)(1). 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, and conversely, if the specification explicitly sets forth an improvement but in a conclusory manner the examiner should not determine the claim improves technology. As discussed in the 101 rejection, above, the claims recite the abstract idea of recommending item sets. The claims further recite additional elements including a computing device, comprising: a radio frequency identification (RFID) reader; a display; and a processor configured to: capture, via the RFID reader of the mobile computing device, an RFID tag; and train a classification model via a plurality of input data sets including one or more item identifiers. While these elements are recited, they are merely peripherally incorporated in order to implement the abstract idea of recommending item sets. For example, while Applicant cited the specification at [0017-0018][0025], noted improvements such as reducing computational resources used in generating recommendations, minimizing recommendations that are ignored by customers, increasing the accuracy of recommendations, and reducing the possible search space of items and item sets are improvements directed towards the abstract idea of recommending item sets, rather than providing any technical improvement. This is unlike the improvements recognized by the Courts in McRO, where both the claims and specification identified a specific improvement to the technical field of computer animation. Furthermore, while the Specification discusses improving the functioning of computing infrastructure, and enabling client devices to determine recommendations locally, reducing computational burden on the server, these merely represent conclusory statements. Neither the cited paragraphs of the Spec nor the claims provide any technical implementation details as to how the claimed invention is providing an improvement to the functioning of the computer or other technology. The claimed process, while arguably resulting in more accurate and efficient recommendations, is not providing a technical improvement. Accordingly, this argument is not persuasive, and the rejection has been maintained.
With regards to Applicant’s Remarks regarding Example 3 of the USPTO Subject Matter Eligibility Examples (Remarks Pages 7-8), Examiner notes that these examples are merely hypothetical, and only intended to be illustrative of the claim analysis under the MPEP. These examples are to be interpreted based on the fact patterns set forth in each example, as other fact patterns may have different eligibility outcomes. Furthermore, the claims of Example 3 were found to be eligible because they added meaningful limitations to the claimed abstract idea, such that they amounted to more than mere computer implementation, and not simply performing the idea via a computer. The instant claims provide no analogous improvement, as discussed in the above paragraphs, as the additional elements are recited at a high level and peripherally incorporated in order to implement the abstract idea. Accordingly, the rejection has been maintained.
Applicant further argues “[the elements] as recited in claim 1 [are] unquestionably a practical application, particularly for entities to efficiently reduce computational resources and improve computational efficiency” (Remarks Page 9). Examiner respectfully disagrees. As discussed above, the additional elements of the claims are insufficient for integration into a practical application. For example, “determining… an item set identifier” is activity directed towards the abstract idea of recommending item sets. While the limitation recites that this is performed via execution of the trained classification model, this amounts to merely implementing the abstract idea in a computing environment, with no technical improvement apparent via the claimed additional elements. While Applicant cites improvements to computational processing efficiency, these are not apparent via the implementation of the abstract idea in the claims, nor the specification. Accordingly, this argument is not persuasive, and the rejection has been maintained.
Applicant’s arguments filed with respect to the rejection of claims under 35 USC 103 have been fully considered but are rendered moot under new grounds of rejection.
Applicant argues that the claims overcome the currently cited prior art because “Ahuja and Beniwal do not disclose… [the limitations of the independent claims]… the customer client device 100 of Ahuja may be ‘a smart refrigerator or a smart pantry system’… each of a refrigerator and a pantry is not mobile” (Remarks Pages 11 and 12). Examiner respectfully disagrees. Examiner notes that previously cited Ahuja [0011] discloses that the customer can be a personal computing device. While Ahuja [0016] discloses that “for example, the customer client device 100 may be a smart refrigerator or a smart pantry system,” this is merely an example of an embodiment of the personal computing device. The remaining cited portion of Ahuja [0016], disclosing that the customer client device 100 may include components such as RFID scanners, does not limit the customer client device to a refrigerator, as there are several instances in the disclosure of Ahuja (see at least [0078-0079]), which disclose that the customer client device is a mobile device, and provides information regarding a customer’s acquired items, for example through RFID tags that data to the customer client device 100. In light of these cited portions of Ahuja, Examiner notes that Ahuja has been further relied upon to teach capturing, via a radio frequency identification (RFID) reader of a mobile computing device associated with a user, a first item identifier of a first item retrieved by the user from an RFID tag affixed to the first item. Accordingly, this argument is not persuasive.
Applicant further argues that the amended claims overcome the currently cited prior art because “the customer client device [of Ahuja] does not ‘determine, at the mobile computing device, whether the first item identifier matches…” (Remarks Pages 12 and 13). Examiner notes that Ahuja has not been relied upon in the current 103 rejection to teach determining, at the mobile computing device. Rather, newly cited Garner has been relied upon to teach this particular limitation and round out the claim as a whole. Accordingly, this argument is rendered moot under new grounds of rejection in view of Garner.
With regards to Applicant’s arguments that independent claim 9 overcomes the currently cited prior art at least for reciting similar features as independent claim 1, and additionally that previously cited Chang and Charles do not cure the deficiencies of Ahuja and Beniwal (Remarks Page 14), Examiner respectfully disagrees. As discussed above, independent claim 1 (and Independent Claim 9) currently stands rejected under 35 USC 103 in view of the newly cited combination of Ahuja and Garner. Accordingly, this argument is rendered moot under new grounds of rejection in view of Garner.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZACHARY R DONAHUE whose telephone number is (571)272-5850. The examiner can normally be reached M-F 8a-5p.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein can be reached at (571) 272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ZACHARY RYAN DONAHUE/Examiner, Art Unit 3689
/MARISSA THEIN/Supervisory Patent Examiner, Art Unit 3689
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