DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to the original application filed on 5/20/2025 and the Remarks and Amendments filed on 9/30/2025. Acknowledgment is made with respect to a claim of priority to Chinese Application CN202311351239.9 filed on 10/18/2023 and PCT Application PCT/CN2024/118410 filed on 9/12/2024.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-4, 6, and 10-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “in a testing phase, three commonly-used Amazon datasets are used for comparison experiments, namely, Clothing, Sports, and Baby” (emphasis added). This limitation contains two clarity issues. First, the element “commonly-used” is a relative term which renders the claim indefinite. The term “commonly used” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. What is a commonly-used dataset versus some other form of dataset? Please explain. Second, the term “Amazon datasets” makes use of a trade name. This trade name is used in a claim as a limitation to identify or describe a particular material or product. See MPEP § 2173.05(u). For examination purposes, the limitation will be interpreted to mean “in a testing phase, three2-4, 6, and 10-17 depend on indefinite claim 1, and are also rejected under 35 USC § 112(b) by virtue of this dependency. Claims 18 and 19 include the steps of claim 1, and are also rejected under 35 USC § 112(b) for the same reasons as claim 1. Appropriate correction is required.
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, 6, and 10-19 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis of the claims will follow the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (“2019 PEG”).
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1). If the claim does fall within one of the statutory categories, the second step in the analysis is to determine whether the claim is directed to a judicial exception (Step 2A). The Step 2A analysis is broken into two prongs. In the first prong (Step 2A, Prong 1), it is determined whether or not the claims recite a judicial exception (e.g., mathematical concepts, mental processes, certain methods of organizing human activity). If it is determined in Step 2A, Prong 1 that the claims recite a judicial exception, the analysis proceeds to the second prong (Step 2A, Prong 2), where it is determined whether or not the claims integrate the judicial exception into a practical application. If it is determined at step 2A, Prong 2 that the claims do not integrate the judicial exception into a practical application, the analysis proceeds to determining whether the claim is a patent-eligible application of the exception (Step 2B). If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim integrates the judicial exception into a practical application, or else amounts to significantly more than the abstract idea itself.
Claim 1
Step 1: The claim recites a recommendation method; therefore, it is directed to the statutory category of a process.
Step 2A Prong 1: The claim recites, inter alia:
(S1) constructing heterogeneous data comprising a user-item interaction matrix and multimedia content data of an item: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of constructing heterogeneous data, which is performed through mathematical computation as evidenced by paragraphs [0015-0019] of the originally filed specification.
(S2) extracting a multimedia content feature of the item from the multimedia content data using a pre-training model: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of extracting features from content data, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper, or is a mathematical concept of extracting features from data, which is performed through mathematical computation as evidenced by paragraph [0021] of the originally filed specification.
(S3) constructing an item association matrix based on the multimedia content feature: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of constructing an association matrix, which is performed through mathematical computation as evidenced by paragraphs [0023-0035] of the originally filed specification.
(S4) learning a user representation matrix and an item representation matrix based on a deep graph neural model: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of learning matrices based on a model, which is performed through mathematical computation as evidenced by paragraphs [0036-0042] of the originally filed specification.
(S5) minimizing, based on an information bottleneck theory, mutual information between the multimedia content feature and representation information of the multimedia content feature to compute a first loss function: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of minimizing information based on an information bottleneck theory to produce a loss function, which is performed through mathematical computation as evidenced by paragraphs [0043-0047] of the originally filed specification.
(S6) reconstructing the user-item interaction matrix based on the user representation matrix and the item representation matrix to compute a second loss function: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of reconstructing a matrix to compute a loss function, which is performed through mathematical computation as evidenced by paragraphs [0048-0054] of the originally filed specification.
(S7) combining the first loss function and the second loss function to perform multi-task learning to update parameters of the deep graph neural model until the deep graph neural model converges: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of combining loss functions to update a model, which is performed through mathematical computation as evidenced by paragraphs [0055-0062] of the originally filed specification.
separately predicting a target interaction probability of each user for the item to determine a target interaction matrix, so as to achieve item recommendation: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of predicting a target interaction probability, which is performed through mathematical computation as evidenced by paragraphs [0055-0062] of the originally filed specification.
for each user, 1 item that the user interacts with is randomly selected as the test set, and the rest of the interaction data is used as the training set; for each user-item interaction record, 1 item that the user has not interacted with is randomly sampled to form a triple for model training; all the items that the user has not interacted with are ranked where the recall rate and the normalized discounted cumulative gain are used as evaluation criteria: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of selecting particular data for inclusion in different datasets, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
classifying a plurality of specific modals corresponding to the multimedia content data: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of classifying models, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
establishing a mapping relationship between the plurality of specific modals and the plurality of sub-training models: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of establishing relationships between modals and models, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0198] of the originally filed specification.
determining the user-item interaction matrix as a first matrix subset, and transposing the first matrix subset to obtain a second matrix subset; determining the item association matrix as a third matrix subset: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of determining matrices, which is performed through mathematical computation as evidenced by paragraphs [0067 and 0104] of the originally filed specification.
constructing a first representation propagation matrix based on the first matrix subset, the second matrix subset, and the third matrix subset: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of constructing matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0214; 0219] of the originally filed specification.
calculating a degree matrix of the first representation propagation matrix: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of calculating a degree matrix, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0221] of the originally filed specification.
normalizing the first representation propagation matrix by multiplying the first representation propagation matrix by the degree matrix to obtain a second representation propagation matrix; Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of normalizing matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0221] of the originally filed specification.
randomly generating an initialized user representation matrix and an initialized item co-representation matrix via Gaussian distribution; Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of generating matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0226] of the originally filed specification.
computing a multimedia content representation matrix of the item by using a predetermined multilayer perceptron: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of computing matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0226] of the originally filed specification.
fusing the initialized item co-representation matrix with the multimedia content representation matrix to determine the item representation matrix; Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of fusing matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0226] of the originally filed specification.
fusing the initialized user representation matrix with the item representation matrix to determine a Oth-layer node representation matrix; Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of fusing matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0226] of the originally filed specification.
inputting the Oth-layer node representation matrix into a predetermined graph neural network, and taking the second representation propagation matrix as an iterative coefficient to obtain a plurality of intermediate node representation matrices respectively corresponding to a plurality of convolutional layers in the predetermined graph neural network: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of processing matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0226] of the originally filed specification.
based on the number of the plurality of convolutional layers in the predetermined graph neural network, aggregating the plurality of intermediate node representation matrices and the Oth-layer node representation matrix to obtain a final node representation matrix: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of aggregating matrices, which is performed through mathematical computation as evidenced by paragraphs [0055-0067; 0226] of the originally filed specification.
Step 2A Prong 2: The claim does not recite any additional limitations which integrate the abstract idea into a practical application. Specifically, the additional elements consist of “using a pre-training model”, “the multimedia content data corresponds to a plurality of specific modals; the representation information of the multimedia content is a multimedia content representation matrix; and the first loss function is an information bottleneck loss function; the second loss function is a reconstruction loss function; the heterogeneous data further comprises an item set; in a testing phase, three commonly-used Amazon datasets are used for comparison experiments, namely, Clothing, Sports, and Baby; for each user … the pre-training model comprises a plurality of sub-training models predetermined”.
The additional elements of “using a pre-training model” amount to reciting only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is not clear how the pre-training model is used to extract features from content data. Thus, the additional elements amount to no more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer (see MPEP § 2106.05(f)).
The additional elements of “the multimedia content data corresponds to a plurality of specific modals; the representation information of the multimedia content is a multimedia content representation matrix; and the first loss function is an information bottleneck loss function; the second loss function is a reconstruction loss function; the heterogeneous data further comprises an item set; in a testing phase, three commonly-used Amazon datasets are used for comparison experiments, namely, Clothing, Sports, and Baby; for each user … the pre-training model comprises a plurality of sub-training models predetermined” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h).
Thus, even when viewed individually and as an ordered combination, these additional elements do not integrate the abstract idea into a practical application and the claim is thus directed to the abstract idea.
Step 2B: Finally, the claim taken as a whole does not contain an inventive concept which provides significantly more than the abstract idea.
The additional elements of “using a pre-training model” amount to reciting only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished because it is not clear how the pre-training model is used to extract features from content data. Thus, the additional elements amount to no more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer (see MPEP § 2106.05(f)).
The additional elements of “the multimedia content data corresponds to a plurality of specific modals; the representation information of the multimedia content is a multimedia content representation matrix; and the first loss function is an information bottleneck loss function; the second loss function is a reconstruction loss function; the heterogeneous data further comprises an item set; in a testing phase, three commonly-used Amazon datasets are used for comparison experiments, namely, Clothing, Sports, and Baby; for each user … the pre-training model comprises a plurality of sub-training models predetermined” amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h).
Taken alone or in combination, the additional elements of the claim do not provide an inventive concept and thus the claim is subject-matter ineligible.
Claim 2
Step 1: A process, as above.
Step 2A Prong 1: The claim recites various equations to expand upon the mathematical concepts of S1-S7 of claim 1. The claim therefore recites a serious of steps (1.1-7.3) that recite various mathematical concepts that are performed through mathematical computations, as evidenced by paragraphs [0015-0072] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 3
Step 1: A process, as above.
Step 2A Prong 1: The claim recites various equations to expand upon the mathematical concepts of S3 of claim 1. The claim therefore recites a serious of steps (4.3) that recite various mathematical concepts that are performed through mathematical computations, as evidenced by paragraphs [0061-0072] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 4
Step 1: A process, as above.
Step 2A Prong 1: The claim recites, inter alia:
determining a mapping relationship between a plurality of users in the user set and individual sub-data in the multimedia content data, so as to obtain a plurality of objective data to characterize an interaction relationship between the user set and the item set: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of determining a mapping relationship between users and sub-data, which is performed through mathematical computation as evidenced by paragraphs [0016-0019] of the originally filed specification.
constructing the user-item interaction matrix based on the plurality of objective data: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of constructing a user-item interaction matrix, which is performed through mathematical computation as evidenced by paragraphs [0016-0019] of the originally filed specification.
Step 2A Prong 2, Step 2B: The additional element “obtaining an item set and a user set, wherein the item set comprises the multimedia content data, and the user set comprises a plurality of user data information corresponding to the multimedia content data” is an insignificant extra-solution activity required for any uses of the abstract ideas (see MPEP § 2106.05(g)), and is a well-understood, routine, conventional activity (see MPEP § 2106.05(d)(II)(i); “Receiving or transmitting data over a network”). Taken alone or in combination, the additional elements of the claim do not provide an inventive concept, integrate the abstract ideas into a practical application, or provide significantly more than the abstract ideas of the claim and thus the claim is subject-matter ineligible.
Claim 6
Step 1: A process, as above.
Step 2A Prong 1: The claim recites, inter alia:
analyzing a similarity of the plurality of specific modals: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of analyzing modals, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
determining a plurality of similarity matrices corresponding to the plurality of specific modals and a similarity matrix set: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of determining similarity matrices, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
sparsifying and sorting the plurality of similarity matrices to obtain a target sequence in which a plurality of elements are sequentially arranged in a descending order: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of sparsifying and sorting matrices, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
selecting first n elements from the target sequence to determine the item association matrix among a plurality of items and an association matrix set, wherein n is a predetermined value: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mental process of selecting elements from a sequence to determine a matrix, which is an evaluation or observation that is practically capable of being performed in the human mind with the assistance of pen and paper.
Step 2A Prong 2, Step 2B: The claim doesn’t recite additional elements that integrate the abstract ideas into a practical application, or provide significantly more than the abstract ideas of the claim and thus the claim is subject-matter ineligible.
Claim 10
Step 1: A process, as above.
Step 2A Prong 1: The claim recites an equation to expand upon the mathematical concepts of S1-S7 of claim 1. The claim therefore recites a step that recites a mathematical concept that is performed through mathematical computations, as evidenced by paragraph [0101] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 11
Step 1: A process, as above.
Step 2A Prong 1: The claim recites various equations to expand upon the mathematical concepts of S1-S7 of claim 1. The claim therefore recites a serious of steps that recite various mathematical concepts that are performed through mathematical computations, as evidenced by paragraphs [0104-0108] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 12
Step 1: A process, as above.
Step 2A Prong 1: The claim recites, inter alia:
performing dimensionality reduction on a multimedia feature matrix set using a PCA algorithm to obtain a dimensionality-reduced multimodal feature matrix: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of performing dimensionality reduction on a matrix set, which is performed through mathematical computation.
calculating, based on the information bottleneck theory, a Hilbert-Schmid tindependence criterion between the dimensionality-reduced multimodal feature matrix and the multimedia content representation matrix to obtain the information bottleneck loss function: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of calculating a criterion, which is performed through mathematical computation.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 13
Step 1: A process, as above.
Step 2A Prong 1: The claim recites an equation to expand upon the mathematical concepts of S1-S7 of claim 1. The claim therefore recites a step that recites a mathematical concept that is performed through mathematical computations, as evidenced by paragraph [0114] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 14
Step 1: A process, as above.
Step 2A Prong 1: The claim recites, inter alia:
processing the final user representation matrix and the final item representation matrix by using a predetermined sigmoid activation function: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of processing matrices using an activation function, which is performed through mathematical computation.
predicting an interaction probability of each user for the item to reconstruct the user-item interaction matrix: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of predicting a probability, which is performed through mathematical computation.
based on a plurality of predicted interaction probabilities and all parameters involved in reconstructing the user-item interaction matrix, calculating the reconstruction loss function: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of calculating a loss function, which is performed through mathematical computation.
Step 2A Prong 2, Step 2B: The additional element “wherein the second loss function is a reconstruction loss function” amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h). Taken alone or in combination, the additional elements of the claim do not provide an inventive concept, integrate the abstract ideas into a practical application, or provide significantly more than the abstract ideas of the claim and thus the claim is subject-matter ineligible.
Claim 15
Step 1: A process, as above.
Step 2A Prong 1: The claim recites various equations to expand upon the mathematical concepts of S1-S7 of claim 1. The claim therefore recites a serious of steps that recite various mathematical concepts that are performed through mathematical computations, as evidenced by paragraphs [0121-0126] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 16
Step 1: A process, as above.
Step 2A Prong 1: The claim recites, inter alia:
establishing a multitask optimization objective function based on the information bottleneck loss function and the reconstruction loss function; wherein the multitask optimization objective function corresponds to to-be-optimized parameters: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of establishing an objective function, which is performed through mathematical computation.
solving the multitask optimization objective function by a gradient descent method to update the to-be-optimized parameters: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of solving an objective function, which is performed through mathematical computation.
determining a corresponding parameter when the multitask optimization objective function converges to a minimum value, as an optimal parameter after updating the to- be-optimized parameters: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of determining a parameter when the function converges, which is performed through mathematical computation.
based on the optimal parameter, separately predicting a target interaction probability of each user for the item to determine a target interaction matrix, so as to achieve item recommendation: Under its broadest reasonable interpretation in light of the specification, this limitation encompasses the mathematical concept of predicting a target interaction probability, which is performed through mathematical computation.
Step 2A Prong 2, Step 2B: The additional element “wherein the first loss function is an information bottleneck loss function, and the second loss function is a reconstruction loss function” amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h). Taken alone or in combination, the additional elements of the claim do not provide an inventive concept, integrate the abstract ideas into a practical application, or provide significantly more than the abstract ideas of the claim and thus the claim is subject-matter ineligible.
Claim 17
Step 1: A process, as above.
Step 2A Prong 1: The claim recites various equations to expand upon the mathematical concepts of S1-S7 of claim 1. The claim therefore recites a serious of steps that recite various mathematical concepts that are performed through mathematical computations, as evidenced by paragraphs [0134-0137] of the originally filed specification.
Step 2A Prong 2, Step 2B: The claim does not recite any additional elements that are sufficient to integrate the judicial exceptions into a practical application or amount to significantly more than the judicial exception and thus the claim is subject-matter ineligible.
Claim 18
Claim 18 recites an electronic device (step 1: a machine) using a processor and memory to perform the steps of claim 1, which by MPEP 2106.05(f) (“apply it”) cannot integrate an abstract idea into a practical application or provide significantly more than the abstract idea by itself, and is thus rejected for the same reasons set forth in the rejection of claim 1.
Claim 19
Claim 19 recites a non-transitory computer-readable storage medium (step 1: a manufacture) using a processor and program to perform the steps of claim 1, which by MPEP 2106.05(f) (“apply it”) cannot integrate an abstract idea into a practical application or provide significantly more than the abstract idea by itself, and is thus rejected for the same reasons set forth in the rejection of claim 1.
Response to Arguments
Applicant’s arguments and amendments, filed on 9/30/2025, with respect to the 35 USC § 112(b) rejection of the pending claims have been fully considered but are persuasive only with respect to the 112(b) issues identified in the previous office action. The pending claims are presently rejected under 35 USC § 112(b) for the reasons mentioned in the updated rejection above.
Applicant’s arguments and amendments, filed on 9/30/2025, with respect to the 35 USC § 101 rejection of the pending claims have been fully considered but are not persuasive.
With respect to Step 2A, Prong 1, Applicant’s arguments are not persuasive to overcome the determination that claim 1 remains directed towards abstract ideas in the form of mental processes and mathematical concepts. Although the claim is framed in the context of multimedia content recommendation, the independent claims recite various steps that are all mathematical operations or mental judgments or evaluations that fall squarely within the “mathematical concepts” or “mental processes” grouping of abstract ideas under the 2019 PEG. The independent claims describe the manipulation of data using generic machine learning and graph-based models without improving how the computer itself operates. Merely limiting the claimed calculations to a “recommendation” or “multimedia” context does not render the claims any less abstract.
With respect to Step 2A, Prong 2, Applicant’s arguments are not persuasive to overcome the determination that claim 1 remains directed towards abstract ideas without additional elements that integrate the abstract ideas into a practical application. The additional elements cited – such as use of a “pre-trained model”, “information bottleneck loss”, “graph neural network”, and “multi-task learning” – are all recited at a a high level of generality and merely describe generic data processing operations implemented in conventional computing hardware. None of these elements impose a meaningful limitation that applies or uses the abstract ideas of the claims in a way that improves the functioning of a computer. It appears that any alleged technical improvement or integration into a practical application is reflected in the abstract ideas of the claim. Abstract ideas alone cannot reflect the technical improvements. See MPEP §2106.05(a).
With respect to Step 2B, Applicant’s arguments are not persuasive to overcome the determination that claim 1 remains directed towards abstract ideas without additional elements that provide significantly more than the abstract ideas. The recited features – including use of common loss functions, multi-layer neural networks, and evaluation using particular datasets – represent either further abstract ideas in the form of mental processes or mathematical concepts or are directed towards field of use exceptions that do not render the claims eligible in view of 101. The independent claims’ testing and evaluation steps are claimed in such a way that they recite either mathematical concepts or mental processes. These newly added limitations recite abstract ideas and, as stated above, abstract ideas alone cannot reflect a technical improvement. These testing and evaluation steps do not provide any non-conventional or non-routine component or additional elements that are comparable to Example 47, Claim 3 of the PEG.
Accordingly, Applicant’s arguments and amendments are not persuasive, and the 35 USC § 101 rejection of the pending claims is maintained.
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.
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/BRENT JOHNSTON HOOVER/Primary Examiner, Art Unit 2127