DETAILED ACTION
This non-final rejection is responsive to the Request for Continued Examination (RCE) filed January 7, 2026. Claims 1, 11, 12, and 15 are currently amended. Claims 13, 14 and 21 are cancelled. Claim 23 has been added. Claims 1-12, 15-20, 22 and 23 are pending in this application.
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 1-12, 15-20, 22 and 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 11 and 15 recite determine user engagement data associated with the collection of queries and the collection of items; determining relevance levels of the relevant training item and the irrelevant training item with respect to the training query based on the training feature vectors and user engagement data of the training data set; prior to receiving a first query from an electronic device associated with a next user, select, from the collection of items, a plurality of items to be provided in response to a first query based on the user engagement data, the plurality of items including a first item that was previously engaged by at least one prior user in response to a plurality of second queries; determine feature vectors of the first query, the plurality of selected items, and the plurality of second queries; determine a plurality of messages for the plurality of selected items associated with the first query based on the feature vectors, including determining a first message of the first item based on the plurality of second queries; determine a query feature vector of the first query based on the plurality of messages including the first message of the first item; and rank the plurality of selected items associated with the first query into an ordered item list based on the query feature vector of the first query. The broadest reasonable interpretation of these steps is that the steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally determine user engagement data, determine relevance levels, determine feature vectors, select items prior to receiving a query, determine a plurality of messages, determine a query feature vector, and rank items.
The limitation “build a graph-based relevance model of the collection of queries and the collection of items, including iteratively adjusting model parameters of the graph-based relevance model including the encoder network based on the relevance levels indicating a triplet loss associated with the training data set” requires specific mathematical calculations (triplet loss function) to perform the adjusting of parameters of the graph-based relevancy model and therefore encompasses mathematical concepts.
This judicial exception is not integrated into a practical application. The additional limitations “communicate with a plurality of client devices that are coupled to the system via one or more communication networks to collect a collection of queries, provide information of a collection of items, and obtain user responses to the collection of items” and “in response to receiving the first query from the next user, extract the ordered item list, and present information of the plurality of items based on the ordered item list on a screen of the electronic device associated with the next user” are mere data gathering and output recited at a high level of generality, and thus are insignificant extra-solution activity. See MPEP 2106.05(g).
The limitations of performing “building a graph based relevance model…including extracting training feature vectors from a training query, a relevant training item, and an irrelevant training item of a training data set using an encoder network applied in the graph-based relevance model”; “applying the graph-based relevance model” to perform selecting, determining and ranking steps; and “using the encoder network” to determine feature vectors of the first query provide nothing more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. The examiner notes that the claims include high level recitation of training and application of a model.
Further, the limitations “a non-transitory memory,” “processor,” and “electronic device” are recited at a high level of generality and amount to no more than mere instructions to apply the exception using generic computer components. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application, and the claims are directed to the judicial exception.
Claims 1, 11, and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the recitations of “communicate with a plurality of client devices that are coupled to the system via one or more communication networks to collect a collection of queries, provide information of a collection of items, and obtain user responses to the collection of items” and “in response to receiving the first query from a next user, extract the ordered item list, and present information of the plurality of items based on the ordered item list on a screen of an electronic device associated with the next user” are recited at a high level of generality such that they amount to receiving or transmitting data over a network or presenting offers and is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
The performing “building a graph based relevance model…including extracting training feature vectors from a training query, a relevant training item, and an irrelevant training item of a training data set using an encoder network applied in the graph-based relevance model”; “applying the graph-based relevance model” to perform selecting, determining and ranking steps; and “using the encoder network” to determine feature vectors of the first query provide nothing more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Further, the limitations “a non-transitory memory,” “processor,” and “electronic device” amount to no more than mere instructions to apply the exception using generic computer components. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
Dependent claims 2, 19 and 22 recite wherein the first item has a respective query feature vector for each of the plurality of second queries, and the first message of the first item is determined by combining the respective query feature vectors of the plurality of second queries associated with the first item using semantic weights. The broadest reasonable interpretation of this step is that the step falls within the mental process groupings of abstract ideas because it covers concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally combine vectors.
The claims do not recite any additional elements, and thus the judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent claims 3 and 20 recite wherein ranking the plurality of items associated with the first query further comprises: determining a relevance level between the first query and each of the plurality of items based on the query feature vector of the first query, wherein the plurality of items are ranked for the first query based on the relevance level associated with each of the plurality of items. The broadest reasonable interpretation of these steps is that the steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally determine relevance.
The claims do not recite any additional elements, and thus the judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent claim 4 recites wherein ranking the plurality of items associated with the first query further comprises: determining an item feature vector for each of the plurality of items, wherein the relevance level between the first query and each of the plurality of items is determined based on the query feature vector of the first query and the item feature vector of the respective item. The broadest reasonable interpretation of this step is that the step falls within the mental process groupings of abstract ideas because it covers concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally determine an item feature vector for each item.
The claim does not recite any additional elements, and thus the judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent claim 5 recites wherein for each of the plurality of items, the relevance level is determined based on a dot product of the query feature vector of the first query and the item feature vector of the respective item. The broadest reasonable interpretation of this step is that the step falls within the mental process groupings of abstract ideas because it covers concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally determine a dot product.
The claim does not recite any additional elements, and thus the judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent claim 6 recites wherein determining the item feature vector for each of the plurality of items further includes determining the item feature vector of the first item, which further comprises: identifying the plurality of second queries to which the first item is provided in response; for each of the plurality of second queries associated with the first item, determining a respective message of the respective second query by combining a plurality of item features of a plurality of second items provided in response to the respective second query; and determining the item feature vector of the first item based on the respective messages of the plurality of second queries; wherein the first item is ranked in the plurality of items associated with the first query based on the query feature vector of the first query and the item feature vector of the first item. The broadest reasonable interpretation of these steps is that the steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally perform the determining and identifying steps.
The claim does not recite any additional elements, and thus the judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent claims 7 and 8 recites wherein the first query is associated with a collection of items that has been engaged with users when provided to the users in response to the first query, and selecting the plurality of items from the collection of items based on an edge weight of each of the plurality of items, wherein the plurality of items includes a predefined number of items in the collection of items. The broadest reasonable interpretation of these steps is that the steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally select items based on edge weight.
The judicial exception is not integrated into a practical application and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the addition element of a memory storing instructions to perform the “selecting” amounts to no more than mere instructions to apply the exception using a generic computer component.
Dependent claim 9 recites wherein each of the plurality of items is selected in accordance with a determination of at least one of the following conditions: (1) that a number of times when the respective item is selected as a query result is greater than a first time; and (2) a number of times when the respective item is selected for review is greater than a second number. The broadest reasonable interpretation of this step is that the step falls within the mental process groupings of abstract ideas because it covers concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally determine when a number of times is greater than a first time or second number.
The claim does not recite any additional elements, and thus the judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Dependent claim 10 recites determining the edge weight of each of the plurality of items based on one or more of a number of times when the respective item is selected as a query result, a number of times when the respective item is selected for review, a number of times when the respective item is selected as a candidate result, and a number of times when the respective item is associated with a cursor hovering action during a duration of time. The broadest reasonable interpretation of this step is that the step falls within the mental process groupings of abstract ideas because it covers concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally determine the edge weight.
The judicial exception is not integrated into a practical application and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the addition element of a memory storing instructions to perform the “determining” amounts to no more than mere instructions to apply the exception using a generic computer component.
Dependent claim 12 recites wherein the plurality of items includes an isolated item that was not previously provided in response to any query; generating an item feature vector of the isolated item; and determining a new message of the isolated item based on the item feature vector of the isolated item, the plurality of messages including the new message. The broadest reasonable interpretation of these steps is that the steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally generate an item feature vector and determine a new message based on the item feature vector.
The judicial exception is not integrated into a practical application and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element of applying the encoder network to generate item feature vector amounts to no more than mere instructions to apply the exception using a generic computer component.
Dependent claim 16 recites the additional element “obtaining an engagement graph connecting a collection of items and a collection queries to each other, wherein the engagement graph is updated periodically, according to a predefined scheduled, or in response to a user request”. The judicial exception is not integrated into a practical application because the obtaining limitation represents adding insignificant extra-solution activity. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because “obtaining” is recited at a high level of generating and amount to storing and retrieving information in memory and is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
Dependent claim 17 recites the additional element wherein the first query is newly received after a last update corresponding to the engagement graph. The judicial exception is not integrated into a practical application because the newly receiving limitation represents adding insignificant extra-solution activity. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitation is recited at a high level of generating and amount to receiving or transmitting data over a network and is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
Dependent claim 18 recites wherein the engagement graph includes the first query, the plurality of items, and the plurality of second queries, and after a last update corresponding to the engagement graph, one or more engagement relationships have been updated between the first query and the plurality of items and/or between the first item and the plurality of second queries. The broadest reasonable interpretation of this step is that the step falls within the mental process groupings of abstract ideas because it covers concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The human mind can mentally generate and update an engagement graph.
The judicial exception is not integrated into a practical application and the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no additional elements.
Dependent claim 23 recites the additional elements: store query-item information of the collection of queries and the user responses associated with the collection of items including the user engagement data in a database; organize the query-item information stored in the database based on the graph-based relevance model, including storing the ordered item list associated with the first query in the database; and receive the first query from the next user after the ordered item list is made available in the database; wherein after the first query is received, the ordered item list is extracted from the database, and the information of the plurality of items is presented, without ranking the plurality of selected items in real time in response to the first query. The judicial exception is not integrated into a practical application because the storing, organizing, receiving, extracting and presenting limitations represents adding insignificant extra-solution activity.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the storing, organizing, receiving, extracting and presenting limitations are recited at a high level of generality and amount to “receiving or transmitting data over a network”, “storing and retrieving information in memory” and “presenting offers” and are thus well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II.
Response to Arguments
Applicant's arguments filed January 7, 2026 have been fully considered but they are not persuasive. Applicant argues that the claims do not recite an abstract idea because the specification states that “automated item ranking and presentation, as disclosed herein, particularly for large platforms…is only possible with the aid of computer-assisted machine-learning algorithms and techniques, such as the disclosed graph-based relevance model 224. In some embodiments, item ranking processes including the trained graph-based relevance model 224 are used to perform operations that cannot practically be performed by a human, either manually or mentally with assistance…” (paragraph 71). However, this language from the specification doesn’t negate the fact that certain limitations of the claimed invention (i.e. those listed above under step 2A, prong 1) can be performed mentally.
Applicant argues that the independent claims recite “a graph-based relevance model” and cannot be practically performed in the human mind, and further that the mental process grouping cannot be expanded to encompass “building a graph-based relevance model of the collection of queries and the collection of items.” However, the examiner does not entirely assert that this limitation falls under the mental process groupings of abstract ideas. Instead, the examiner addresses the “building a graph-based relevance model of the collection of queries and the collection of items, including extracting training vectors…using an encoder network” as an additional element that amounts to no more than applying the abstract idea with a computer. The “determining” portion of the building limitation recites a mental process because a user can mentally determine relevance levels of relevant and irrelevant training items based on training feature vectors and user engagement data of the training set. Lastly, the ”iteratively adjusting…a triplet loss associated with the training data set” portion of the building limitation recites a mathematical concept because it requires specific mathematical calculations (triplet loss function) to perform the training/adjusting of the graph-based relevancy model.
Applicant further argues that the new features (i.e. building a graph-based relevance model, selecting a plurality of items, determining a plurality of messages, determining a query feature vector, and ranking the plurality of selected items) integrate the abstract idea into a practical application, linking the use of the judicial exception to a particular technological environment and field of user, and amount to significantly more than the judicial exception. The examiner disagrees. The selecting a plurality of items, determining a plurality of messages, determining a query feature vector, and ranking the plurality of selected items limitations all fall under the mental process grouping of abstract ideas because they represent steps that can be performed mentally in the human mind using observation, evaluation and judgment. As stated above, “building a graph-based relevance model” includes limitations directed to a mental process (i.e. determining relevance level) and mathematical concept (i.e. iteratively adjusting model parameters based on triplet loss), and further includes a limitation (i.e. extracting feature vectors using an encoder network) that amounts to applying abstract idea using a computer. Therefore, the judicial exception is not integrated into a practical application and the claim does not include features that amount to significantly more than the abstract idea.
Applicant further argues that the incorporation of “an encoder network” is Applicant’s attempt to incorporate features associated with the “building a graph-based relevance model” as suggested by the examiner. However, this limitation amounts to adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer. The encoder network is recited at a high level of generality. The “encoder network” also merely indicates a field of use or technological environment (neural networks) in which the abstract idea is performed and thus fails to add an inventive concept to the claims.
Applicant further argues that the features of new claim 23 are directed to an improvement to the technical field of computation resource management in the context of enhancing a computer system’s response rate to a query. The examiner disagrees. The limitations recited in claim 23 represent storing and retrieving information in memory, receiving and transmitting data over a network, and presenting offers, all of which are well-understood, routine and conventional. The examiner does not find any limitations that support an improvement to the functioning of a computer.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALICIA M WILLOUGHBY whose telephone number is (571)272-5599. The examiner can normally be reached 9-5:30, EST, M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ajay Bhatia can be reached at 571-272-3906. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALICIA M WILLOUGHBY/Primary Examiner, Art Unit 2156 February 20, 2026