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 .
Claims Status
Claims 2-6 and 9-20 have been cancelled.
Claims 1 and 7-8 remain pending and stand rejected.
Response to Arguments
I. Applicant’s arguments made with respect to the rejection under 35 USC 101 have been fully considered but are not persuasive.
Applicant initially argues against the Examiner’s determination in Step 2A (prong One) that the claims recite an abstract idea. As in previous responses, the Examiner initially reminds Applicant that the mere presents of ‘physical components’ also does not negate the recitation of the abstract idea. In Step 2A (Prong One) examiners evaluate whether the claim recites a judicial exception, i.e. whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. The Examiner maintains that the claims clearly set forth or describe a commercial process by setting forth or describing the procedure for recommending products.
With respect to inputting the clicked commodity sequence, the unclicked commodity sequence and the disliked commodity sequence into an encoder based on a multi-head attention mechanism for encoding, and, inputting the training set into the commodity recommendation model these elements have been evaluated on Prong Two as additional elements. Despite the presence of these and other additional elements, the finding under Prong One is maintained.
With respect to Prong Two, the elements emphasized by Applicant are recited only at a high level of generality and utilized to automate the abstract idea recited in the claim. Though Applicant alleges a technical improvement, the problem solved by the invention is one that arises specifically in the commercial realm: “Embodiments of the present application provide a disentangled commodity recommendation method and apparatus, a device and a storage medium, and aim at improving accuracy of recommending commodities to users.” (see: 0005). Applicant’s previous arguments reiterate this point (e.g., “Firstly, the present application utilizes the method to solve the technical problem in a specific occasion, such as the commodity recommendation model” (see: Remarks dated 4/3/2025, p. 15)), as do the current arguments (e.g., “a method to provide recommendations of commodities to a user based on previously clicked commodities, unclicked commodities, and dislike commodities” (p. 12)). Neither the specification nor the claims reflect an improvement to the functioning of the computer or another technology or technical field.
Furthermore, though Applicant alleges that “existing multi-feedback recommendation technology doesn’t disentangle the interests of the user”, this remains an improvement to the recommendation process itself (and thus the abstract idea itself). Even in view of paragraph 0079 and 0090 neither the claims nor the specification manifest an improvement to the computer itself or another technology or technical field. If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology (see MPEP 2106.05(a); MPEP 2106.04(d)(1)).
Neither the specification nor the claims provide the requisite detail necessary such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement to the underlying technology of machine learning. The specification and claims provide little details or restriction on how encoding may be performed from the technical perspective, or how the multi-head attention mechanism functions, other than their utilization of certain data to support performance of the abstract commercial process. As written, the claims merely used generic computing technology in facilitation of the abstract idea.
Accordingly, the rejection has been maintained as updated below.
Claim Rejections - 35 USC § 101
(Judicial Exception)
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 and 7-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Regarding claims 1 and 7-8, under Step 2A claims 1 and 7-8 recite a judicial exception (abstract idea) that is not integrated into a practical application and does not provide significantly more.
Under Step 2A (prong 1), and taking claim 1 as representative, claim 1 recites a disentangled commodity recommendation method, implemented based on a commodity recommendation model, wherein the method comprises:
receiving information of commodities to be recommended and historical behavioral information of a user, the historical behavioral information comprising a clicked commodity sequence, an unclicked commodity sequence, a disliked commodity sequence and behavioral time information of the user, and the information of commodities to be recommended comprising names of the commodities to be recommended, categories of the commodities to be recommended and usage of the commodities to be recommended;
filtering the clicked commodity sequence and the unclicked commodity sequence according to the disliked commodity sequence to obtain representations of interested commodities of the user;
filtering the representations of the interested commodities according to the behavioral time information and the information of the commodities to be recommended to obtain representations of historical interested commodities of the user;
clustering and aggregating the representations of the historical interested commodities to obtain a plurality of disentangled representations of the user; and
determining whether the commodities to be recommended are the interested commodities of the user according to the plurality of disentangled representations;
providing the commodities to be recommended that are interested commodities of the user; and,
presenting to the user the commodities to be recommended that are the interested commodities of the user;
wherein filtering the clicked commodity sequence and the unclicked commodity sequence according to the disliked commodity sequence to obtain the representations of the interested commodities of the user, comprises:
obtain representations of clicked commodities, representations of unclicked commodities and representations of disliked commodities;
filtering the representations of the clicked commodities, the representations of the unclicked commodities, and the representations of disliked commodities to obtain the representations of the interested commodities of the user;
wherein training steps of the commodity recommendation model comprise:
taking a set composed of a plurality of groups of user information and commodity information corresponding to the plurality of groups of user information as a training set…; and
selecting, by the commodity recommendation model, a sample with corresponding difficulty in the training set for learning according to a current learning state, adjusting difficulty distribution of the sample at a corresponding rate, and obtaining a trained commodity recommendation model after learning;
wherein filtering the representations of the interested commodities of the user according to the behavioral time information of the user and the information of the commodities to be recommended to obtain the representations of the historical interested commodities of the user, comprises:
performing corresponding weight assignment on the representations of the interested commodities according to the behavioral time information;
performing corresponding weight assignment on the representations of the interested commodities according to the information of the commodities to be recommended; and
taking the representations of the interested commodities after the weight assignment as the representations of the historical interested commodities of the user.
These limitations recite ‘certain methods of organizing human activity’, such as by performing commercial interactions and/or managing personal behavior (see: MPEP 2106.04(a)(2)(II)). This is because claim 1 recites limitations for filtering and analysis of information of a user in order to recommend items. This represents the performance of a marketing and/or sales activity, which is a commercial interaction and falls under organizing human activity (see MPEP 2106.04(a)(2)(II)((B)). Furthermore, the filtering and analysis related to historical content represents managing personal behavior (MPEP 2106.04(a)(2)(II)((C)(i) and (ii)).
Accordingly, under step 2A (prong 1) claim 1 recites an abstract idea because claim 1 recites limitations that fall within the “Certain methods of organizing human activity” grouping of abstract ideas.
Under Step 2A (prong 2), the abstract idea is not integrated into a practical application. The Examiner acknowledges that representative claim 1 does recite additional elements, including a recommendation system,
(arguably) a commodity recommendation model,
an application on a user’s device,
a browser of the user’s device,
inputting the clicked commodity sequence, the unclicked commodity sequence and the disliked commodity sequence into an encoder based on a multi-head attention mechanism for encoding, and
inputting the training set into the commodity recommendation model.
Although reciting these additional elements, taken alone or in combination these elements are not sufficient to integrate the abstract idea into a practical application. This is because the additional elements of claim 1 are recited 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, the additional elements are insufficient to integrate the abstract idea into a practical application 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 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.
In view of the above, under Step 2A (prong 2), claim 1 does not integrate the recited exception into a practical application.
Under Step 2B, examiners should evaluate additional elements individually and in combination to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). In this case, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
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. they do not amount to “significantly more” than the exception itself). 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 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.
Furthermore, the additional elements fail to provide significantly more also because the claim simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. For example, the additional elements of claim 1 utilize operations the courts have held to be well-understood, routine, and conventional (see: MPEP 2106.05(d)(II)), including at least:
receiving or transmitting data over a network,
storing and retrieving information in memory,
presenting offers.
Even considered as an ordered combination (as a whole), the additional elements of claim 1 do not add anything further than when they are considered individually.
In view of the above, representative claim 1 does not provide an inventive concept (“significantly more”) under Step 2B, and is therefore ineligible for patenting.
Regarding claim 7 (computer readable storage medium) and claims 8 (an electronic device), claims 7-8 recite at least substantially similar concepts and elements as recited in claims 1 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art.
Notably, adding further additional elements such as a CRSM, executable instructions (e.g., claim 7), and a memory, processor, and computer program (e.g., claim 8) fail to confer eligibility on these claims. This is again because the claims merely apply the exception on 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), generally link the exception to a technological environment, and (at best) append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception As such, claims 7-8 are rejected under at least similar rationale as discussed above with respect to claims 1.
Allowable Subject Matter
Though rejected on other grounds, claims 1 and 7-8 are allowable over the prior art for at least the reasons set forth in the Non-Final Action mailed 1/22/2025 and refined by the Final Action mailed 4/24/2025. The Examiner maintains the discussion of the remaining deficiencies and incorporates those reasons from the respective actions above are incorporated herein. The Examiner also re-emphasizes the discussion of improper hindsight bias, while noting that the newly amended features only act to further reinforce the Examiner’s finding of nonobviousness.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure
Kumar (US 20170061286) discloses a recommendation method that utilizes aggregated interaction data (e.g., a user's purchase history, user device, clickstream, internet cookies, view history, etc.,) (see: abstract, 0075, 0085).
PTO form 892-U discloses utilization of machine learning techniques to avoid bombarding customers with irrelevant marketing communications (see: abstract).
PTO form 892-V discusses the use of RNN technology in understanding the purchase funnel comprised of observable online activities (i.e., search queries, site visits, online article views, and ad interactions) which online users perform before converting on an advertiser. In particular, given a trail (sequence) of relevant online activities that a user has performed, an estimate of the user’s funnel stage for a given advertiser in an interpretable and scalable manner can be obtained (see: Introduction, Fig. 1, Section 3).
Applicant's amendment necessitated the any changes to the ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM J ALLEN whose telephone number is (571)272-1443. The examiner can normally be reached Monday-Friday, 8:00-4:00.
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WILLIAM J. ALLEN
Primary Examiner
Art Unit 3625
/WILLIAM J ALLEN/Primary Examiner, Art Unit 3619