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 .
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 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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.
Status of Claims
Claims 1-20 remain pending, and are rejected.
Response to Arguments
Applicant’s arguments filed on 11/25/2025 with respect to the rejection under 35 U.S.C. 101 have been fully considered, but are not persuasive for at least the following rationale:
Applicant’s arguments filed on 11/25/2025 with respect to the rejection under 35 U.S.C. 101 for claims directed to a judicial exception are not persuasive.
Notably, on pages 15-16 of the Applicant’s Remarks, arguments are made that the claims amount to significantly more than the abstract idea. The Applicant draws comparisons to Bascom to argue that the claims recite an inventive concept of using a decision tree-based machine learning model with various aspects training encoders to determine embeddings, and tokenizing product names.
Examiner respectfully disagrees. While the claims recite various encoders and decision trees, these elements are only applied to the abstract idea to perform calculations for the abstract idea. How these type of elements function or how they are improved are not reflected in the claims or the specification. General training of an encoder, or any machine learning algorithm, does not constitute a meaningful limitation of the abstract idea, as general training is inherent to any machine learning. The various recited elements only provide outputs to be used in the abstract idea for determining similarity scores and associated product types. As disclosed in specification paragraph [0040], the encoder can be any of word2vec, BM25, GloVe, etc. As such, it is evident that they are not any particular element, and that any generic functionality of encoders can be used. In paragraph [0037], it is disclosed that a model based on decision trees or other machine learning techniques may be used. The various additional elements recited in the claims are any generic component that is merely applied to the abstract idea to perform various calculations for the abstract idea, but the particular functionality of these elements are clearly not vital to the invention. In Bascom, the combination of elements did not merely apply generic components to an abstract idea, but applied the judicial exception in a meaningful way beyond providing a general link to a particular technological environment by taking advantage of the ability of the ISPs to identify individual accounts that communicate with the ISP server to associated a request for internet content with a specific individual account. As discussed above, there is not such a leveraging of technical abilities to provide an inventive concept or technical improvement.
In view of the above, the rejection under 35 U.S.C. 101 has been maintained below.
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 1-20 are rejected under 35 U.S.C. 101 because the claims are directed to a judicial exception without significantly more.
Step 1:
Claims 1-10 are directed to a system, which is an apparatus. Claims 11-20 are directed to a method, which is a process. Therefore, claims 1-20 are directed to one of the four statutory categories of invention.
Step 2A (Prong 1):
Taking claim 1 as representative, claim 1 sets forth the following limitations reciting the abstract idea of identifying complementary products for an anchor item:
tokenizing, using one or more tokenizers, an anchor-product-type name of an anchor product type for an anchor item;
aggregating, using one or more pooling functions, one or more anchor word embeddings, into an anchor-product-type-name vector for an anchor-product-type name;
determining a respective complementary-product-type-name vector for a respective complementary-product-type name of each of at least one complementary product type, for the anchor product type, tokenizing the anchor-product-type name, and aggregating using the one or more pooling functions;
determining a respective product-type-name similarity score between the anchor-product-type-name vector and the respective complementary-product-type-name vector for each of the at least one complementary product type;
determining at least one associated product type based at least in part on a product-type-level threshold and the respective product-type-name similarity score for each of the at least one complementary product type;
determining at least one associated item for the anchor item based at least in part on the at least one associated product type and at least one recommended item for the anchor item after determining the respective complementary-product-type-name vector and after the respective complementary-product-type-name vector is used to determine the at least one associated product type, wherein at least one recommended item is determined based at least in part on historical transaction data associated with the anchor item;
transmitting information regarding the at least one associated to the user.
The recited limitations above set forth the process for identifying complementary products for an anchor item. These limitations amount to certain methods of organizing human activity, including commercial or legal transactions (e.g. agreements in the form of contracts, advertising, marketing or sales activities or behaviors, etc.). The claims are directed to identifying product types of anchor and complementary items and comparing for similarity thresholds to then identify items to display to the user from the determined complementary product type (see specification: [0003] disclosing the problem of users siloed into one type of category and not purchasing across types of categories), which is an advertising and marketing activity.
Such concepts have been identified by the courts as abstract ideas (see: MPEP 2106.04(a)(2)).
Step 2A (Prong 2):
Examiner acknowledges that representative claim 1 recites additional elements, such as:
one or more processors;
one or more non-transitory computer-readable media storing computing instructions;
a computer network;
a user interface;
training a product-type word encoder based on a training dataset that includes one or more tokenized historical search words;
using a decision tree-based machine learning model;
using a Noise-resistant complementary item recommendation CIRS (NEAT) model;
Taken individually and as a whole, representative claim 1 does not integrate the recited judicial exception into a practical application of the exception. The additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Furthermore, this is also because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement a judicial exception with a particular machine, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
While the claims recite one or more processors and non-transitory computer-readable media, these elements are recited with a very high level of generalization. They are merely recited in passing as executing the steps of the abstract idea without any further involvement. Specification paragraph [0018] discloses that the processors are any type of computational circuit, not limited to microprocessors, microcontrollers, etc. Specification paragraph [0017] discloses that the memory can be any of USB-equipped electronic devices, hard drives, CD-ROM, DVD, or any other suitable media. As such, it is evident that these elements are any generic computing components that merely implement the abstract idea on a general computing device, such that the abstract idea is performed within a computing environment. The computing network is also any generic networking of devices, such as the internet (specification paragraph: [0029]), and is also recited in passing as the method of transmitting information. The computing network is merely another generic computing element to implement the abstract idea within a computing environment. The user interface is also not disclosed in the specification with any particularity, and is merely disclosed as displaying the items to the user. In specification paragraph [0040], the encoder can be any of word2vec, BM25, GloVe, etc. In paragraph [0037], it is disclosed that a model based on decision trees or other machine learning techniques may be used. The specific functionality of these elements are not vital to the claims, and these elements are only applied to the abstract idea to provide a calculation/output for the abstract idea As such, it is evident that the additional elements are generic computing components that are merely applied to the abstract idea, and provide a general link to a computing/network environment.
In view of the above, under Step 2A (Prong 2), representative claim 1 does not integrate the recited exception into a practical application (see: MPEP 2106.04(d)).
Step 2B:
Returning to representative claim 1, taken individually or as a whole, the additional elements of claim 1 do not provide an inventive concept (i.e. whether the additional elements amount to significantly more than the exception itself). As noted above, the additional elements recited in claim 1 are recited in a generic manner with a high level of generality and only serve to implement the abstract idea on a generic computing device. The claims result only in an improved abstract idea itself and do not reflect improvements to the functioning of a computer or another technology or technical field. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed process ultimately amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment.
Even when considered as an ordered combination, the additional elements of claim 1 do not add anything further than when they are considered individually.
In view of the above, claim 1 does not provide an inventive concept under step 2B, and is ineligible for patenting.
Regarding Claim 11 (method): Claim 11 recites at least substantially similar concepts and elements as recited in claim 1 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art. As such, claims 11 is rejected under at least similar rationale as provided above regarding claim 1.
Dependent claims 2-10 and 12-20 recite further complexity to the judicial exception (abstract idea) of claim 1, such as by further defining the algorithm of identifying complementary products for an anchor item, and do not recite any further additional elements. Thus, each of claims 2-10 and 12-20 are held to recite a judicial exception under Step 2A (Prong 1) for at least similar reasons as discussed above.
Under prong 2 of step 2A, the additional elements of dependent claims 2-10 and 12-20 also do not integrate the abstract idea into a practical application, considered both individually or as a whole. More specifically, dependent claims 2-10 and 12-20 rely on at least similar elements as recited in claim 1. Further additional elements are also acknowledged (e.g., a database (claim 4)); however, the additional elements of claims 2-10 and 12-20 are recited only at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Further, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
Secondly, this is also because the claims fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Taken individually and as a whole, dependent claims 2-10 and 12-20 do not integrate the recited judicial exception into a practical application of the exception under step 2A (prong 2).
Lastly, under step 2B, claims 2-10 and 12-20 also fail to result in “significantly more” than the abstract idea under step 2B. The dependent claims recite additional functions that describe the abstract idea and use the computing device to implement the abstract idea, while failing to provide an improvement to the functioning of a computer, another technology, or technical field. The dependent claims fail to confer eligibility under step 2B because the claims merely apply the exception on generic computing hardware and generally link the exception to a technological environment.
Even when viewed as an ordered combination (as a whole), the additional elements of the dependent claims do not add anything further than when they are considered individually.
Taken individually or as an ordered combination, the dependent claims simply convey the abstract idea itself applied on a generic computer and are held to be ineligible under Steps 2B for at least similar rationale as discussed above regarding claim 1. Thus, dependent claims 2-10 and 12-20 do not add “significantly more” to the abstract idea.
Subject Matter Free of Prior Art
Claims 1-20 are determined to have overcome the prior art of rejection and are free of prior art, however, the claims remain rejected under 35 U.S.C. 101, as set forth above.
Claims 1-20 are found to overcome the prior art rejection for the reasons as set forth below.
Claim 1 recites the claims features of:
determining the at least one associated product type based at least in part on a product-type-level threshold and the respective product-type-name similarity score for each of the at least one complementary product type;
determining at least one associated item for the anchor item based at least in part on the at least one associated product type and at least one recommended item for the anchor item, wherein the at least one recommended item is determined based at least in part on historical transaction data associated with the anchor item;
The closest prior art was found to be as follows:
Hughes (US 20210374830 A1) recites [0034] – “By using product types in a taxonomy (e.g., in the steps 40 and/or 42), the systems and methods herein can also determine accessory recommendations for items with which a user has not interacted with previously (e.g., for which there is no data at the step 38). This is possible because accessory recommendations may be determined for an item type, which covers specific items that may not yet have user interaction data (or specific items for which there is limited user interaction data). In addition, higher levels or nodes of a taxonomy may be substituted (e.g., at the steps 42 and/or 76) in various methods herein because item types at lower levels in a taxonomy may sometimes be too granular to broadly represent a product type that is useful for determining accessory recommendations. For example, a parent node related to televisions may be categorized into leaf nodes relating to organic light emitting diode (OLED) televisions, smart televisions, ultra-high definition (HD) televisions, etc. As a result, the best accessory for a television may not be apparent when assessing the leaf nodes related to specific televisions, but may be identified when assessing a parent node relating to televisions more broadly. Accordingly, a structure of an item taxonomy may provide useful information for determining accessories for product types or determining accessory product types from anywhere in an item taxonomy (not just between a same taxonomy level)”. However, Hughes does not disclose determining a vector for anchor-product-type name of an anchor product or a complementary-product-type-name for a complementary-product-type name of the complementary product types, and determining a similarity score of the vectors.
Bermperidis (US 20240054138 A1) recites [0040] – “Generally, similarities and dissimilarities are computed for each seed and candidate item pair for the embeddings. Thus, regarding the overlapping item flow 422, at block 425, candidate items are identified that satisfy a similarity threshold with respect to the seed item based on the embeddings (e.g., description, topic, and tag embeddings). In some embodiments, the similarity threshold may be based on a relevance score. Additionally, or alternatively, the similarity threshold may be a predetermined percentile of the candidate items based on the relevance score or the like. Then, at block 430, overlapping items are identified based on the candidate items identified satisfying the similarity threshold”. Notably, however, Bermperidis does not disclose vectors or embeddings specifically for the product types, or using both the similarity and historical transaction data to determine at least one associated item for the anchor item.
Wang (US 20220138826 A1) recites [0072] – “the output as represented in the vector space 209 is computed based on a word embedding vector model computing semantic similarity between words. For example, a vocabulary set (e.g., all the words in the vector space 209) may first be converted into input vectors via an input vector encoding (e.g., one hot encoding). For example, the words “model T Case” may be converted into the vector [1,0,0,0,0]. This vector representation shows five dimensions, where each value corresponds to ordered words (e.g., each word in a set of trained queries and titles) and whether the word is TRUE or present. Because “model T case” are the only words being run through the word embedding model in this example, the integer 1 is used to indicate its representation. “model T case” does not contain any of the other words within it (e.g., “blue”) so the other values are represented as 0. In some embodiments, based on generating the softmax function above or the output layer of the neural network, an output embedding vector representation can be generated, which is indicative of the actual coordinates that a vector will be plotted in vector space 209 based on semantic similarity to other words and/or averaging or otherwise combining the output embedding vectors for all of the words within the message vectors”. However, Wang does not disclose vectors or embeddings specifically for the product types, or using both the similarity and historical transaction data to determine at least one associated item for the anchor item.
NPL Reference U (see PTO-892 Reference U mailed on 8/28/2025) discloses a system using text-based and image-based embeddings recommendations for complementary items. Similarity scores are calculated between features in the embedding space to identify the highest weighted scores to output. Notably, however, NPL Reference U does not disclose determining associated product types and making vectors of the product type names to then identify associated items.
Therefore, none of the cited references disclose or render obvious each and every feature of the claimed invention and the claimed invention is determined to be free of the prior art. Although individually the claimed features could be taught, any combination of references would teach the claimed limitations using a piecemeal analysis, since references would only be combined and deemed obvious based on knowledge gleaned from the applicant's disclosure. Such a reconstruction is improper (i.e., hindsight reasoning). See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). The examiner emphasizes that it is the interrelationship of the limitations that renders these claims free of the prior art/additional art.
Therefore, it is hereby asserted by the Examiner that, in light of the above, that the claims 1-20 are free of prior art as the references do not anticipate the claims and do not render obvious any further modification of the references to a person of ordinary skill in art.
Conclusion
THIS ACTION IS MADE FINAL. 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 TIMOTHY J KANG whose telephone number is (571)272-8069. The examiner can normally be reached Monday - Friday: 7:30 - 5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Maria-Teresa Thein can be reached at 571-272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/T.J.K./Examiner, Art Unit 3689
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 1/30/2026