DETAILED ACTION
Status of Claims
Claims 1, 5-6, 15, and 18-20 are currently amended.
Claims 4, 9-14, 17, and 22 have been canceled.
Claims 1-3, 5-8, 15-16, 18-21, and 23-24 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 .
Response to Arguments
35 USC 101
Applicant's arguments and amendments filed 01/14/2026 with respect to the 35 USC 101 rejection have been fully considered but they are not persuasive. Applicant argues that he claims do not recite a judicial exception. Examiner respectfully disagrees. As was discussed in the previous 35 USC 101 rejection, Claim 1 recites the abstract idea of providing relevant item attribute information. Specifically, claim 1 recites the abstract idea of: Receiving a request associated with a user to display one or more items; Determining a context in which to display based on the request; Retrieving a set of items for display based on the request, each item of the set associated with one or more attributes; For each item of the set: determining a group including each combination of the item of the set, an attribute of the item of the set, and the determined context, determining an information gain for each combination of the group, and selecting an attribute for display in conjunction with the item based on the determined information gains; generating for display to the user, displaying an item of the set and displaying the corresponding selected attribute for the item of the set in conjunction with the item of the set; obtaining training dataset including a plurality of training examples, each training example including a combination of an item, an attribute of the item, and a display context, and each training example having a value indicating an information gain form displaying the attribute of the item in conjunction with the item displayed in the display context; generating a predicted information gain form displaying the attribute of the item of the training example in conjunction with the item of the training example displayed in the display context of the training example; scoring using a loss function and the value of the training example; updating one or more parameters by backpropagation based on the scoring until one or more criteria are satisfied; and storing the updated one or more parameters. The abstract idea identified is considered to be a certain method of organizing human activity because it recites a is a commercial or legal interaction because it is a sales activity and/or relates to business relations. Applicant argues that the claims are similar to example 37 claim 2 in that they involve rearranging and automatically adjusting the attribute information in a user interface. Examiner respectfully disagrees. Claim 2 of Example 37 did not recite ANY judicial exceptions and was therefore found eligible in Step 2A, prong 1. Here, representative claim 1 includes a plurality of recitations that recite an abstract idea considered to be certain methods of organizing human activity.
Applicant further argues, citing Specification paragraph [0002], that the claims are integrated into a practical application under Step 2A, prong 2 in that they recite a technical solution regarding a problem of a user interface on a user computing device having limited space to display relevant attribute information about items. Examiner respectfully disagrees. Paragraph [0002] of Applicant’s Specification discloses “When the online concierge system displays items to a user through an interface, an attribute may be displayed in conjunction with each item. Displaying the attribute in conjunction with an item allows a user to ascertain information about the item form the interface to evaluate whether to include ethe item in an order form the interface.” There is nothing in paragraph [0002], nor anywhere else in the Specification that discloses the problem of limited space to display relevant attribute information in a user interface. Applicant’s argument is merely a conclusory statement with no explanation as to how the invention improves the functionality of the user interface/computing device and is therefore insufficient to demonstrate that the claims improve technology. Simply including the use of a trained machine learning model does not mean that there has been a technological solution to a technical problem. The instant claims are not directed to improving an existing technological process but are directed to improving the commercial task of providing attribute information of items. As such, the claims do not recite specific technological improvements.
For at least these reasons, Examiner maintains the previous 35 USC 101 rejection.
35 USC 103
Applicant's arguments and amendments filed 01/14/2026 have been fully considered but they are not persuasive. Applicant argues that Sridhar does not disclose training a model to generate an information gain score associated with an item attribute being displayed in a user interface alongside an item in a particular context or that the a prediction that a particular attribute displayed alongside a particular item will have a higher or lower likelihood of causing a user to perform some interaction (as opposed to predicting whether a user will reorder an item). Examiner respectfully disagrees. Examiner first notes that Applicant is relying on a more narrow definition of an information gain and what is being predicted. Examiner suggests Applicant amend what is meant by an “information gain” in order to overcome the Sridhar reference. Sridhar discloses collecting data about what was displayed etc. and previous transactions in order to be used as training data for machine learning and determine probability of identifying items to be ordered on specific items on specific days. Sridhar is able to predict confidence level of probability of user selecting previous item to be reordered. Therefore, displaying a previously ordered item during selected time periods, may have a high confidence of a user preforming the action of reordering that item. Examiner is interpreting this to be the value indicating an information gain. Under broadest reasonable interpretation, predicting that a user will do the action of reordering an item is considered to be “some interaction” that a user performs. For at least these reasons, Applicant’s arguments are not found to be persuasive.
Examiner notes in light of amendments (e.g., including claim 4 in claim 1, etc.), a new grounds of rejection is made in further view of Fernandez Galan (US 11,816,720).
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 1-3, 5-8, 15-16, 18-21, and 23-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. The claims recite an abstract idea. This 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 eligibility analysis the claims are directed to statutory categories. MPEP 2106.03. Specifically, the method, as claimed in claims 1-3 and 5-8, is directed to the process. Additionally, the computer program product comprising a non-transitory computer readable medium, as claimed in claims 15-16 and 18-19, is directed to a machine. Finally, the system, as claimed in claims 20-21 and 22-24, is directed to an apparatus.
While the claims fall within statutory categories, under Step 2A, Prong 1 of the eligibility analysis (MPEP 2106.04), the claimed invention recites the abstract idea of providing relevant item attribute information. Specifically, representative claim 1 recites the abstract idea of:
Receiving a request associated with a user to display one or more items;
Determining a context in which to display based on the request;
Retrieving a set of items for display based on the request, each item of the set associated with one or more attributes;
For each item of the set: determining a group including each combination of the item of the set, an attribute of the item of the set, and the determined context, determining an information gain for each combination of the group, and selecting an attribute for display in conjunction with the item based on the determined information gains;
generating for display to the user, displaying an item of the set and displaying the corresponding selected attribute for the item of the set in conjunction with the item of the set;
obtaining training dataset including a plurality of training examples, each training example including a combination of an item, an attribute of the item, and a display context, and each training example having a value indicating an information gain form displaying the attribute of the item in conjunction with the item displayed in the display context;
generating a predicted information gain form displaying the attribute of the item of the training example in conjunction with the item of the training example displayed in the display context of the training example;
scoring using a loss function and the value of the training example;
updating one or more parameters by backpropagation based on the scoring until one or more criteria are satisfied; and
storing the updated one or more parameters.
The abstract idea identified above is considered to be a certain method of organizing human activity because it recites a is a commercial or legal interaction because it is a sales activity and/or relates to business relations. Thus, representative claim 1 recites an abstract idea.
Under Step 2A, Prong 2 of the eligibility analysis, if it is determined that the claims recite a judicial exception, it is then necessary to evaluate whether the claims recite additional elements that integrate the judicial exception into a practical application of that exception. MPEP 2106.04(d). The courts have identified limitations that did not integrate a judicial exception into a practical application include limitations merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f). MPEP 2106.04(d). In this case, representative claim 1 includes additional elements such as a computer system comprising a processor and computer-readable medium, a user device, an interface, one or more interfaces, and attribute selection model. Although reciting such additional elements, the additional elements do not integrate the abstract idea into a practical application because they merely amount to no more than an instruction to apply the abstract idea using a generic computer or merely use a computer as a tool to perform the abstract idea. These additional elements are described at a high level in Applicant's specification without any meaningful detail about their structure or configuration. Similar to the limitations of Alice, representative claim 1 merely recites a commonplace business method (i.e., providing item information) being applied on a general-purpose computer. See MPEP 2106.05(f). Thus, the claimed additional elements are merely generic elements and the implementation of the elements merely amounts to no more than an instruction to apply the abstract idea using a generic computer. Since the additional elements merely include instructions to implement the abstract idea on a generic computer or merely use a generic computer as a tool to perform an abstract idea, the abstract idea has not been integrated into a practical application.
Under Step 2B of the eligibility analysis, if it is determined that the claims recite a judicial exception that is not integrated into a practical application of that exception, it is then necessary to evaluate the additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). MPEP 2106.05. In this case, as noted above, the additional elements recited in independent claim 1 are recited and described in a generic manner merely amount to no more than an instruction to apply the abstract idea using a generic computer or merely use a generic computer as a tool to perform an abstract idea.
Even when considered as an ordered combination, the additional elements of representative claim 1 do not add anything that is not already present when they are considered individually. In Alice, the court considered the additional elements “as an ordered combination,” and determined that “the computer components...‘ad[d] nothing. ..that is not already present when the steps are considered separately’... [and] [v]iewed as a whole...[the] claims simply recite intermediated settlement as performed by a generic computer.” Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 217, (2014) (citing Mayo, 566 U.S. at 79, 101 USPQ2d at 1972). Similarly, when viewed as a whole, representative claim 1 simply conveys the abstract idea itself facilitated by generic computing components. Therefore, under Step 2B of the Alice/Mayo test, there are no meaningful limitations in representative claim 1 that transforms the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself.
As such, representative claim 1 is ineligible.
Dependent Claims 2-3 and 5-8 do not aid in the eligibility of independent claim 1. For example, claims 2-3 and 5-8 merely further define the abstract limitations of claim 1. Dependent claims 2-3 and 5-8 do not recite additional elements supplemental those recited in claim 1. Therefore, the additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea for the reasons described above with respect to claim 1.
Thus, dependent claims 2-3 and 5-8 are also ineligible.
Independent claims 15 and 20 recite the same abstract idea represented in representative claim 1. Independent Claim 15 recites the additional elements of a computer program product comprising an non-transitory computer readable medium, processor, user device, interface, and attribute selection model. Independent Claim 20 recites the additional elements of a system comprising one or more processors and a nontransitory computer readable medium, user device, interface, and attribute selection model. The additional elements in Independent claims 15 and 20 do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea for the reasons described above with respect to claim 1.
Similarly, the dependent claims 16, 18-19, 21, and 23-24 do not recite additional elements supplemental those recited in claims 2-3 and 5-8. Therefore, the additional elements to not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea for the reasons described above with respect to claims 2-3 and 5-8, respectively.
Thus, dependent claims 16, 18-19, 21, and 23-24are also 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.
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, 6-8, 15, 19-20, and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sridhar et al. (US 2021/0241353) in view of Dey et al. (US 2022/0327352), and further in view of Fernandez Galan (US 11,816,720).
Regarding Claims 1, 15, and 20, Sridhar discloses A method, performed at a computer system comprising a processor and a computer-readable medium, comprising: (See at least Abstract, paragraph [0029]),
receiving a request from a user device associated with a user to display an interface, the interface including one or more items; (See at least paragraph [0040] disclosing allow users to search for items on site, [0154] disclosing keyword searching for items, [0156], [0197])
determining a context in which the interface is to be displayed based on the request; (See at least paragraph [0055] disclosing determining number of items that can be displayed to user based on size of screen of user computer, [0066], [0075] disclosing displaying predetermined limit of items, [0090], [0190])
retrieving a set of items for display in the interface based on the request, each item of the set associated with one or more attributes; (See at least paragraph [0049] disclosing product database contains information about the products, etc., [0060], [0067], Fig. 6)
for each item of the set: determining a group including each combination of the item of the set, an attribute of the item of the set, and the determined context, determining an information gain for each combination of the group by applying an attribute selection model to a combination (See at least paragraph [0052] disclosing machine learned models to determine set of items to recommend to the user with high level of confidence, [0060], [0067], [0075] disclosing using model to determine likelihood score sand select items with subject to predetermined limit of times that may be displayed on the user interface, [0079] disclosing computing information gain of a certain feature value, Fig. 13);
wherein the attribute selection model is trained by: obtaining a training dataset including a plurality of training examples, each training example including a combination of an item, an attribute of the item, and a display context in which one or more interfaces were displayed, and each training example having a value indicating an information gain from displaying the attribute of the item in conjunction with the item in an interface displayed in the display context; applying the attribute selection model to each training example of the training dataset to generate a predicted information gain from displaying the attribute of the item of the training example in conjunction with the item of the training example in an interface displayed in the display context of the training example (See at least paragraph [0058], [0071], [0073]-[0076], and [0079] disclosing training data regarding the item, attribute, and display information and generating the predicted information gain with the model and training examples).
Sridhar does not expressly provide for selecting an attribute for display in conjunction with the item based on the determined information gains; generating the interface for display to the user, the interface displaying an item of the set and displaying the corresponding selected attribute for the item of the set in conjunction with the item of the set; and causing the user device to display the generated interface.
However, Dey discloses selecting an attribute for display in conjunction with the item based on the determined information gains; generating the interface for display to the user, the interface displaying an item of the set and displaying the corresponding selected attribute for the item of the set in conjunction with the item of the set; and causing the user device to display the generated interface. (See at least Abstract disclosing determining relevant attributes and identifying the one relevant attribute and transmitting to a user interface device for display the categorization of the select data item along with the natural language explanation of the categorization of the select data, [0012] disclosing providing attribute data in natural language explanation of the categorization, [0047], [0048], Fig. 2).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the displayed attribute data as taught by Dey in the attribute model system of Sridhar because it would help better provide explanation as to why some data is the most relevant. See Dey paragraph [0002], [0012].
Neither Sridhar nor Dey expressly provides for scoring the attribute selection model using a loss function and the value of the training example; updating one or more parameters of the attribute selection model by backpropagation based on the scoring until one or more criteria are satisfied; and storing the updated one or more parameters of the attribute selection model.
However, Fernandez Galan discloses scoring the attribute selection model using a loss function and the value of the training example (See at least col 4, lns 36-60 disclosing scoring with a loss function); updating one or more parameters of the attribute selection model by backpropagation based on the scoring until one or more criteria are satisfied (See at least col 4, lns 36-60 disclosing updating the model to minimize difference between prediction of model and ground truth label, etc.); and storing the updated one or more parameters of the attribute selection model (See at least col 11, lns 1-16 disclosing storing updated model data/feature values).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included updates in the training as taught by Fernandez Galan in the attribute selection model system of Sridhar/Dey because improving how the parameters of a model are updated/tuned would help with latency in search results, remove unnecessary expense, and improve the user experience. See Fernandez Galan col 2, lns 30-51.
Regarding Claims 6, 19, and 24, Sridhar, Dey, and Fernandez Galan teach or suggest all of the limitations of claims 1, 15, and 20. Neither Sridhar nor Dey expressly provide for wherein training examples of the training dataset are generated from interactions by information describing display of one or more interfaces to users of a subset including a context in which an interface was displayed, pairs of items and corresponding attributes displayed by the interface, and an indication of a specific action performed by a user of the subset after display of the interface.
However, Fernandez Galan discloses wherein training examples of the training dataset are generated from interactions by information describing display of one or more interfaces to users of a subset including a context in which an interface was displayed, pairs of items and corresponding attributes displayed by the interface, and an indication of a specific action performed by a user of the subset after display of the interface (See at least col 2, lines 18-50, col 6, lns 29-45, and col 7-8, lns 15-67 &1-50 disclosing use of click interactions to help generate training dataset, col 3, lns 39-53 & col 4, lns 54-59 disclosing use of pairs).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included updates in the training as taught by Fernandez Galan in the attribute selection model system of Sridhar/Dey because improving how the parameters of a model are updated/tuned would help with latency in search results, remove unnecessary expense, and improve the user experience. See Fernandez Galan col 2, lns 30-51.
Regarding Claim 7, Sridhar, Dey, and Fernandez Galan teach or suggest all of the limitations of claim 1. Additionally, Sridhar discloses wherein the context is one or more of: search results, a carousel display of items, a list of items, or a request to display a recipe (See at least paragraph [0154] & [0190] disclosing listing of items in response to query).
Regarding Claim 8, Sridhar, Dey, and Fernandez Galan teach or suggest all of the limitations of claim 1. Sridhar does not expressly provide for wherein the interface displays text comprising the selected attribute for the item of the set in conjunction with the item of the set. However, Dey discloses wherein the interface displays text comprising the selected attribute for the item of the set in conjunction with the item of the set (See at least Abstract disclosing determining relevant attributes and identifying the one relevant attribute and transmitting to a user interface device for display the categorization of the select data item along with the natural language explanation of the categorization of the select data, [0012] disclosing providing attribute data in natural language explanation of the categorization, [0047], [0048], Fig. 2).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the displayed attribute data as taught by Dey in the attribute model system of Sridhar because it would help better provide explanation as to why some data is the most relevant. See Dey paragraph [0002], [0012].
Claim(s) 2-3, 16, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sridhar et al. (US 2021/0241353) in view of Dey et al. (US 2022/0327352), in view of Fernandez Galan (US 11,816,720), and further in view of Sikka et al. (US 11,195143).
Regarding Claims 2, 16, and 21, Sridhar, Dey, and Fernandez Galan teach or suggest all of the limitations of claims 1, 15, and 20. However, neither Sridhar nor Dey nor Fernandez Galan expressly provides for wherein selecting the attribute for display in conjunction with the item based on the determined information gains comprises: ranking the combinations of the group based on the information gain determined for each combination of the group; and selecting the attribute included in a combination of the group having at least a threshold position in the ranking.
Sikka discloses wherein selecting the attribute for display in conjunction with the item based on the determined information gains comprises: ranking the combinations of the group based on the information gain determined for each combination of the group; and selecting the attribute included in a combination of the group having at least a threshold position in the ranking. (See at least col 18, lns 23-40 disclosing an information gain ratio threshold and ranking the information gain ratios associated with various pairs).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the threshold rankings as taught by Sikka in the attribute model system of Sridhar/Dey/Fernandez Galan because computing the information gain ratio would help reduce the amount of computation needed. See Sikka col 16, lns 60-67.
Regarding Claim 3, Sridhar, Dey, Fernandez Galan, and Sikka teach or suggest all of the limitations of claim 2. Neither Sridhar nor Dey nor Fernandez Galan expressly provide for wherein the threshold position in the ranking is a highest position in the ranking. However, Sikka discloses wherein the threshold position in the ranking is a highest position in the ranking (See at least col 18, lns 23-40).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have included the threshold rankings as taught by Sikka in the attribute model system of Sridhar/Dey/Fernandez Galan because computing the information gain ratio would help reduce the amount of computation needed. See Sikka col 16, lns 60-67.
Subject Matter Free of Prior Art
Claims 5, 18, and 23 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of subject matter free from prior art:
The Examiner hereby asserts that the totality of the evidence neither anticipates nor renders obvious the particular combination of elements as claimed. That is, the Examiner emphasizes the claims as a whole and hereby asserts that the totality of the evidence fails to set forth, either explicitly or implicitly, an appropriate rationale for combining or otherwise modifying the available prior art to arrive at the claimed invention. The combination of features as claimed would not be obvious to one of ordinary skill in the art because any combination of the evidence at hand to reach the combination of features as claimed would require a substantial reconstruction of Applicant’s claimed invention relying on improper hindsight bias.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRITTANY E BARGEON whose telephone number is (571)272-2861. The examiner can normally be reached Monday-Friday 9:00am to 6:00pm.
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/B.E.B/Examiner, Art Unit 3688
/Jeffrey A. Smith/Supervisory Patent Examiner, Art Unit 3688
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