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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 22 January 2026 has been entered.
Response to Arguments
Applicant's arguments filed in the Amendment B (“Response”) on 22 January 2026 with respect to the rejection under 35 USC 101 have been fully considered but they are not persuasive.
Reducing the cognitive load on a user is not an improvement to the machine, but an improvement made on a user’s ability to search for a product. Further, identifying data, whether it be data found in tables or different nodes (i.e. leaves) of a taxonomy data structure (i.e. hierarchical tree), encompasses a mental process. If the claim limitations, under its broadest reasonable interpretation, covers steps which could be performed in the human mind including an observation, evaluation, judgement of opinion but for the recitation of generic computer components, then it falls within the “mental process” grouping of abstract ideas.
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, 4-11 and 14-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without “significantly more.” Claims 1, 4-11 and 14-20 are directed to receiving a request, identifying the set of items, generating an availability prediction, determining low availability, generating a generic item and sending a list for display, which is considered an abstract idea. Further, the claim(s) as a whole, when examined on a limitation-by-limitation basis and in ordered combination do not include an inventive concept.
Step 1 – Statutory Categories
As indicated in the preamble of the claims, the examiner finds the claims are directed to a process or article of manufacture.
Step 2A – Prong One - Abstract Idea Analysis
Exemplary claim 1 (and similarly claim 11) recites the following abstract concepts, in italics below, which are found to include an “abstract idea”:
A method comprising, at a computer system comprising a processor and memory:
receiving, from a user device, a request to present a set of items to a user of the user device, wherein the set of items corresponds to a product category of a plurality of product categories, wherein the plurality of categories correspond to nodes within a taxonomy data structure, wherein the taxonomy data structure is a hierarchical structure of product categories;
identifying the set of items within the product category by:
identifying a node within the taxonomy data structure corresponding to the product category;
identifying sub-nodes within the taxonomy data structure, wherein the sub-nodes descend from the identified node and correspond to sub-product categories of the product category; and
identifying items within the sub-product categories corresponding to the identified sub-nodes;
generating an availability prediction for each item of the set of items by applying a prediction model to each item of the set of items, wherein the availability prediction for each item of the set of items is a prediction of the likelihood that the item is available at a warehouse location, and wherein the prediction model is a machine learning model trained to predict a probability that an item is available at a warehouse location based on the warehouse location and a plurality of characteristics associated with the item;
determining that the product category has low availability based on the generated availability predictions for the set of items;
responsive to determining that the product category has low availability, generating a generic item for the product category, wherein the generic item represents all items within the product category and within the sub-product categories; and
sending a list of items to the user device for display to the user, wherein the list of items includes the generic item as one of the items, wherein sending the list of items causes the user device to display a graphical user interface comprising a subset of the set of items and the generic item, wherein the subset of items and the generic item are arranged in the graphical user interface based on the availability predictions for each of the subset of items.
The claim features in italics above as drafted, under its broadest reasonable interpretation, are mental processes and/or certain methods of organizing human activity performed by generic computer components. That is, other than reciting “a processor”, “memory”, “a machine learning model trained”, “user device” and “a graphical user interface”, nothing in the claim element precludes the step from practically being performed in the mind or a method of organized human activity. For example, but for the “processor”, “memory”, “machine learning model trained”, “user device” and “graphical user interface” language, “identifying the set of items within the product category by: identifying a node within the taxonomy data structure corresponding to the product category; identifying sub-nodes within the taxonomy data structure, wherein the sub-nodes descend from the identified node and correspond to sub-product categories of the product category; and identifying items within the sub-product categories corresponding to the identified sub-nodes; generating an availability prediction for each item of the set of items by applying a prediction model to each item of the set of items, wherein the availability prediction for each item of the set of items is a prediction of the likelihood that the item is available at a warehouse location, and wherein the prediction model is … to predict a probability that an item is available at a warehouse location based on the warehouse location and a plurality of characteristics associated with the item… determining that the product category has low availability based on the generated availability predictions for the set of items… responsive to determining that the product category has low availability, generating a generic item for the product category, wherein the generic item represents all items within the product category and within the sub-product categories” in the context of this claim encompasses a mental process. If the claim limitations, under its broadest reasonable interpretation, covers steps which could be performed in the human mind including an observation, evaluation, judgement of opinion but for the recitation of generic computer components, then it falls within the “mental process” grouping of abstract ideas. Even further, “receiving a request to present a set of items to a user, wherein the set of items corresponds to a product category of a plurality of product categories, wherein the plurality of categories correspond to nodes within a taxonomy data structure, wherein the taxonomy data structure is a hierarchical structure of product categories.. sending a list of items to the user device for display to the user, wherein the list of items includes the generic item as one of the items, wherein sending the list of items causes… to display… interface comprising a subset of the set of items and the generic item, wherein the subset of items and the generic item are arranged in the … interface based on the availability predictions for each of the subset of items” in the context of this claim encompasses certain methods of organizing human activity. If the claim limitations, under its broadest reasonable interpretation, covers a fundamental economic practice, commercial or legal interaction or managing personal behavior or relationships or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A – Prong Two - Abstract Idea Analysis
This judicial exception is not integrated into a practical application. In particular, the claim only recites five additional elements – “a processor”, “memory”, “a machine learning model trained”, “user device”, “user device associated with a picker” and “a graphical user interface”. The “processor”, “memory”, “machine learning model trained”, “user device”, “user device associated with a picker” and “graphical user interface” are recited at a high-level of generality (i.e., as a generic processor performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer component (MPEP 2106.05(f)). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B - Significantly More Analysis
The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “a processor”, “memory”, “a machine learning model trained”, “user device”, “user device associated with a picker” and “graphical user interface” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply the exception using a generic computer component cannot provide an inventive concept. Further, the background does not provide any indication that the “processor”, “memory”, “machine learning model trained”, “user device”, “user device associated with a picker” and “graphical user interface” are anything other than a generic, off-the-shelf computer component. For these reasons, there is no inventive concept. The claim is not patent eligible.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hunter Wilder whose telephone number is (571)270-7948. The examiner can normally be reached Monday-Friday 8:30AM-5:30PM.
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, Florian Zeender can be reached at (571)272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A. Hunter Wilder/Primary Examiner, Art Unit 3627