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 .
Status of Claims
This action is in reply to the communications filed on January 21, 2026. The Applicants’ Amendment and Request for Reconsideration has been received and entered.
Claims 1-2, 4-9, 11-16, and 18-20 are currently pending and have been examined. Claims 1, 8, and 15 have been amended. Claims 3, 10, and 17 have been canceled.
The previous rejection of claims 8-20 under 35 USC 112(b) has been withdrawn.
Response to Arguments
Applicants’ amendments necessitated any new grounds of rejection.
The previous rejection of claims 8-20 under 35 USC 112(b) has been withdrawn in view of Applicants’ amendments.
Applicants’ arguments regarding the rejection under 35 USC 101 have been fully considered but they are not persuasive. Applicants argue at page 15 of Applicants’ Reply dated January 21, 2026 (hereinafter “Applicants’ Reply”) that “a claim with limitations that cannot practically be performed in the human mind does not recite a mental process” and specifically reference the following steps: “receiving, by the server and from a user via a user interface of a user system over a network, a recommendation request”, “accessing, by the server and from a database and in response to receiving the recommendation request from the user, a data matrix comprising a listing of products that are associated with product profiles”, and “initiating, automatically and in response to the historical electronic activity for the target product being below the threshold, a process to increase a density of the historical electronical activity for the target product.”
The Examiner respectfully disagrees.
Per MPEP 2106.04(a)(2)(III)(A), examples of claims that do not recite mental processes because they cannot be practically performed in the human mind include: a claim to a method for calculating an absolute position of a GPS receiver and an absolute time of reception of satellite signals, where the claimed GPS receiver calculated pseudoranges that estimated the distance from the GPS receiver to a plurality of satellites; a claim to detecting suspicious activity by using network monitors and analyzing network packets; a claim to a specific data encryption method for computer communication involving a several-step manipulation of data; and a claim to a method for rendering a halftone image of a digital image by comparing, pixel by pixel, the digital image against a blue noise mask, where the method required the manipulation of computer data structures (e.g., the pixels of a digital image and a two-dimensional array known as a mask) and the output of a modified computer data structure (a halftoned digital image).
In contrast, claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include: a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind; claims to "comparing BRCA sequences and determining the existence of alterations," where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind; a claim to collecting and comparing known information, which are steps that can be practically performed in the human mind; and a claim to identifying head shape and applying hair designs, which is a process that can be practically performed in the human mind).
Further, per MPEP 2106.04(a)(2)(III)(C), “Claims can recite a mental process even if they are claimed as being performed on a computer.” Thus, merely reciting the use of a computer is not sufficient to recite a technological improvement. MPEP 2106.04(a)(2)(III)(C) further indicates “In evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.”
With these examples in mind, the Examiner respectfully asserts that the claims recite a mental process. First, the Examiner respectfully asserts that the instant claims recite methods that can be done with pen and paper or in the human mind because they recite collecting and comparing known information, i.e., recommending items to users for purchase based on product features. This has been routinely performed mentally or using pen and paper.
For example, a buyer in a store may ask a sales associate for assistance in purchasing a television, which is analogous to receiving a recommendation request. Based on the sales associate’s experience with the televisions in the store, the sale associate may recommend a particular television to the buyer that is a best-selling product, which is analogous to accessing, in response to receiving the recommendation request from the user, a data matrix comprising a listing of products that are associated with product profiles. T
he sales associate may also recommend newer products to the buyer that have not had many sales but that meet the user’s needs and that are similar to the best-selling television the sales associate recommended, which is analogous to initiating, in response to the historical electronic activity for the target product being below the threshold, a process to increase a density of the historical electronical activity for the target product. In other words, the sales associate makes the newer products equivalent to the best-selling product artificially based on the newer products being similar to the best-selling product.
Further, the Examiner respectfully asserts that the claimed invention is being performed on a generic computer. At least in the previous office action and below, the Examiner has identified the recited server the one or more processors and the non-transitory machine-readable storage medium as being recited at a high level of generality (i.e., as generic computer components performing generic computer functions). Further, per paragraph [0011] of Applicants’ published application, a “’server’ is meant to refer to a computing device or system, including processing hardware and process space(s), an associated storage medium such as a memory device or database, and, in some instances, a database application (for example, OODBMS or RDBMS) as is well known in the art.” Thus, the claimed invention is performed on a generic computer.
Accordingly, the Examiner concludes that the claimed invention is a concept performed in the human mind and applicants are merely claiming that concept performed on a generic computer.
Applicants further argue at page 18 of Applicants’ Reply that the “amended claims improve the functioning of database systems and machine learning recommendation engines by addressing the well-recognized technical problem of sparse data matrices in recommendation systems.” Applicants further argue at page 18 that the limitation “initiating, automatically and in response to the historical electronic activity for the target product being below the threshold, a process to increase a density of the historical electronical activity for the target product” represents an improvement “to how database systems handle sparse data matrices. This automatic threshold detection prevents wasted computational resources on products that cannot generate recommendations, improving overall system efficiency.” The Examiner respectfully disagrees.
Per MPEP 2106.04(d), in order to determine if a claim integrates the judicial exception into a practical application, the considerations set forth in MPEP 2106.05 (a)-(c) and (e)-(h) are evaluated. MPEP 2106.04(d) clearly states that “a specific way of achieving a result is not a stand-alone consideration... However, the specificity of the claim limitations is relevant to the evaluation of several considerations including the use of a particular machine, particular transformation and whether the limitations are mere instructions to apply an exception.” The Examiner notes that the considerations include improvements to computer functionality, improvements to any other technology or technical field, and a particular machine or transformation.
Further, per MPEP 2106.05(a), in order to constitute a technical improvement, the specification "must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. 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." Further, per MPEP 2106.05(a), "if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement."
Per MPEP 2106.05(a), improvements to computer functionality include a modification of conventional Internet hyperlink protocol to dynamically produce a dual-source hybrid webpage; inventive distribution of functionality within a network to filter Internet content; a method of rendering a halftone digital image; a distributed network architecture operating in an unconventional fashion to reduce network congestion while generating networking accounting data records; a memory system having programmable operational characteristics that are configurable based on the type of processor, which can be used with different types of processors without a tradeoff in processor performance; technical details as to how to transmit images over a cellular network or append classification information to digital image data; a particular structure of a server that stores organized digital images; a particular way of programming or designing software to create menus; a method that generates a security profile that identifies both hostile and potentially hostile operations, and can protect the user against both previously unknown viruses and "obfuscated code," which is an improvement over traditional virus scanning; an improved user interface for electronic devices that displays an application summary of unlaunched applications, where the particular data in the summary is selectable by a user to launch the respective application; a specific interface and implementation for navigating complex three-dimensional spreadsheets using techniques unique to computers; and a specific method of restricting software operation within a license.
Per MPEP 2106.05(a), some examples that the courts have said “may not be sufficient to show an improvement in computer-functionality” include generating restaurant menus with functionally claimed features; accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer; mere automation of manual processes, such as using a generic computer to process an application for financing a purchase; recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone; affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed; instructions to display two sets of information on a computer display in a non-interfering manner, without any limitations specifying how to achieve the desired result; providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality”; and arranging transactional information on a graphical user interface in a manner that assists traders in processing information more quickly.
With this guidance in mind, the Examiner respectfully asserts that the claims are not directed to a practical application. Regarding the argument that automatic threshold detection prevents wasted computational resources, the Examiner first notes that the claims, as currently recited, do not actually recite the automatic threshold detection. For example, the claims do not actually recite a periodic or continuous monitoring of which products have historical electronic activity that is below a threshold. Instead, the claims merely recite a response to the detecting.
Further, as discussed above, the instant claims merely use a computer as a tool to perform an abstract idea. There is no difference in the operation of the computer resulting from using the claimed invention and thus no technological improvement.
Applicants further argue at page 18 of Applicants’ Reply that the claims create “more robust training datasets” in order to create “semantically meaningful data augmentation.” The Examiner respectfully asserts that this is not a technological improvement but instead appears to be an improvement to an improved recommendation process and thus is an improvement to the abstract idea.
Applicants further argue at pages 18-19 of Applicants’ Reply that the claims are directed to “intelligent threshold-triggered processing that automatically determines when augmentation is needed” and that this “represents a fundamental improvement to how computer systems process and utilize sparse data matrices.” The Examiner respectfully disagrees. As discussed above, the instant claims do not currently recite how the processing is triggered and how it is determined that augmentation is needed. Instead, the claims merely recite a response to the detecting.
Applicants further argue at page 19 of Applicants’ Reply that the instant claims solve “the sparse data matrix problem that prevents recommendation systems from functioning effectively for new products, enables automatic quality maintenance for recommendation accuracy as product catalogs expand, implements self-healing data matrices that maintain functionality without manual intervention, and creates resilient recommendation architectures that can handle dynamic product inventories.” The Examiner respectfully disagrees and asserts that these are not improvements to technology but instead appear to be improvements to the recommendation process and thus are improvements to the abstract idea.
Applicants further argue at page 19 of Applicants’ Reply that the “combination of automatic threshold detection, embedding vector generation, similarity scoring, and weighted boosting creates a non-conventional technical solution.” The Examiner respectfully disagrees with Applicants’ assertion. First, as the Examiner has previously noted above, automatic threshold detection through period or constant monitoring is not actually recited in the claims.
Further, per MPEP 2106.05(I): “Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination. See Mayo, 566 U.S. at 91, 101 USPQ2d at 1973 (rejecting "the Government's invitation to substitute §§ 102, 103, and 112 inquiries for the better established inquiry under § 101 "). As made clear by the courts, the ‘novelty’ of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a Claim falls within the § 101 categories of possibly patentable subject matter.” Intellectual Ventures I v. Symantec Corp., 838 F.3d 1307, 1315, 120 USPQ2d 1353, 1358 (Fed. Cir. 2016) (quoting Diamond v. Diehr, 450 U.S. at 188-89, 209 USPQ at 9). See also Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) ("a claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating § 102 novelty."). In addition, the search for an inventive concept is different from an obviousness analysis under 35 U.S.C. 103. See, e.g., BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQe2d 1236, 1242 (Fed. Cir. 2016) ("The inventive concept inquiry requires more than recognizing that each claim element, by itself, was known in the art. . . . [A]n inventive concept can be found in the non-conventional and non-generic arrangement of known, conventional pieces."). Specifically, lack of novelty under 35 U.S.C. 102 or obviousness under 35 U.S.C. 103 of a claimed invention does not necessarily indicate that additional elements are well-understood, routine, conventional elements. Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101.”
Applicants further argue at page 19 of Applicants’ Reply that, pursuant to the decision in Ex Parte Desjardins, “examiners should not dismiss additional elements as mere ‘generic computer components’ without considering whether such elements confer a technological improvement to a technical problem, especially as to improvements to computer components or the computer system.” Applicants further argue at page 20 of Applicants’ Reply that the specification “describes how the claimed invention addresses well-recognized technical challenges in recommendation systems” such as that “conventional techniques suffer from insufficient historical electronic activity that prevents reliable recommendations.” Applicants further argue at page 20 of Applicants’ Reply that the invention “addresses sparsity in the historical electronic activity of the data matrix”. The Examiner respectfully disagrees. As discussed above, these are not improvements to technology but instead appear to be improvements to the recommendation process and thus are improvements to the abstract idea. In fact, there is no difference in the operation of the computer resulting from using the claimed invention and thus no technological improvement.
Thus, the rejection under 35 USC 101 is maintained.
Applicants’ remaining arguments have been fully considered but they have either been addressed above or they are moot in view of the new grounds of rejection.
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 1-2 and 4-7 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 “initiating, automatically…” but does not indicate whether this step is performed by the server. In light of all the other steps in claim 1 being performed by the server, the Examiner is interpreting this step as also being performed by the server.”
Claims 2 and 4-7 inherit the deficiencies of claim 1.
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 1-2, 4-9, 11-16, and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims 1, 8, and 15 recite a method, an apparatus, and a non-transitory machine-readable medium for recommending products. With respect to claim 1, claim elements accessing a data matrix, initiating a process to increase a density of the historical electronic activity for the target product, identifying a first subset of product profiles, generating an embedding vector of the product profile, computing distances between the embedding vectors, augmenting the historical electronic activity of the target product, weighting a boosting factor, calculating association values, and generating a sorted list of products, as drafted, illustrate a series of steps that, under their broadest reasonable interpretation, cover a mental process. That is, other than reciting that a server performs the method, nothing in the claim precludes the steps from practically being performed in the mind. Claims 8 and 15 recite similar limitations.
The judicial exception is not integrated into a practical application. In particular, claims 1, 8, and 15 recite receiving data, copying, i.e., transmitting/receiving/storing data, and returning information to a user interface, i.e., displaying data. These limitations are considered to recite insignificant extra-solution activity. Further, claims 1 and 15 recite a server and claim 8 recites a set of one or more processors and a non-transitory machine-readable storage medium. These elements are recited at a high level of generality i.e., as generic computer components performing generic computer functions. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Thus, claims 1, 8, and 15 are directed to the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, claims 1, 8, and 15 recite receiving data, copying, i.e., transmitting/receiving/storing data, and returning information to a user interface, i.e., displaying data. Per MPEP 2106.05(q)(II), elements such as receiving or transmitting data over a network, using the Internet to gather data, and storing and retrieving information in memory are considered to be computer functions that are well-understood, routine, and conventional functions. See Versata Dev. Group, inc. v. SAP Am, inc., 793 F.3d 1306, 1334, 115 USPG2d 1681, 1701 (Fed. Cir. 2015). OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1368, 115 USPQ2d 1090, 1093 (Fed. Cir. 2075) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1360, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2074) (computer receives and sends information over a network)).
Further, as discussed above, claims 1 and 15 recite a server and claim 8 recites a set of one or more processors and a non-transitory machine-readable storage medium. These elements are recited at a high level of generality (i.e., as generic computer components performing generic computer functions). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
Additionally, the independent claims recite that one or more machine learning models are used to identify a first subset of product profiles, generate an embedding vector of the product profile of the target product and a set of embedding vectors of one or more product profiles within the first subset of product profiles, and to compute similarity scores. The specification identifies examples of machine learning models to use: multi-label classification models such as k-nearest neighbor models, decision trees, kernel methods, and neural networks. Applicants do not describe the particulars of the models, indicating that the models are sufficiently well-known to a person having ordinary skill in the art. Thus, the Examiner interprets the machine learning models referenced in the claims as being a well-understood, routine, or conventional element.
Claims 2, 4-7, 9, 11-14, 16, and 18-20 depend from claims 1, 8, and 15. Claims 2, 9, and 16 are directed to first product entry and combining the historical activity and are further directed to the abstract idea. Claims 4, 11, and 18 are directed to types of machine learning models and are further directed to the abstract idea. Claims 5, 12, and 19 are directed to calculating an average historical electronic activity and are further directed to the abstract idea. Claims 6-7, 13-14, and 20 are directed to receiving the recommendation request which, as discussed above , is considered to be a computer function that is well-understood, routine, and conventional.
Thus, the claims are not patent eligible.
Novelty/Nonobviousness
Claims 1-2, 4-9, 11-16, and 18-20 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, and 35 USC 101 set forth in this Office action.
In the event the claims are amended, they will be subject to further examination.
With respect to claim 1, the prior art of record, alone or combined, neither anticipates nor renders obvious a method comprising receiving, by the server and from a user via a user interface of a user system over a network, a recommendation request that comprises an indication of a target product and a request for at least one product that complements the target product; accessing, by the server and from a database and in response to receiving the recommendation request from the user, a data matrix comprising a listing of products that are associated with product profiles, the data matrix, that is within the database, having product entries that store historical electronic activity of various users related to respective products within the listing of products, wherein the historical electronic activity for the target product is below a threshold; and initiating, automatically and in response to the historical electronic activity for the target product being below the threshold, a process to increase a density of the historical electronic activity for the target product, wherein the process comprises: identifying, by the server and based at least in part on inputting the product profiles of one or more other products, from the listing of products that are separate from the target product, into one or more machine learning models, a first subset of product profiles that share product characteristics with a product profile of the target product; generating, by the server and via the one or more machine learning models, an embedding vector of the product profile of the target product and a set of embedding vectors of one or more product profiles within the first subset of product profiles; computing, by the server and based at least in part on the one or more machine learning models generating the embedding vector and the set of embedding vectors, distances between the embedding vector of the product profile of the target product and the set of embedding vectors of the one or more product profiles within the first subset of product profiles to obtain similarity scores between the product profile of the target product and the first subset of product profiles, the similarity scores indicating a subset of products from the one or more other products from the first subset of product profiles that have a similarity score above a scoring threshold; augmenting, by the server and at the database that stores the data matrix comprising the listing of products associated with the product profiles, the historical electronic activity of the target product with the historical electronic activity of products within the subset of products indicated based at least in part on the similarity scores to obtain an indication of boosted historical electronic activity of the target product wherein augmenting the target product and the historical electronic activity of the target product further comprises: weighting a boosting factor for each product of the subset of products used to obtain the historical electronic activity of the target product based on the similarity score between the product and the target product; and copying, into a first product entry associated with the target product that is stored within the database, the historical electronic activity of the products in the subset of products that are stored in one or more second product entries within the database, and wherein the boosted historical electronic activity of the target product is obtained based at least in part on copying the historical electronic activity of the products in the subset of products into the first product entry; calculating, by the server, association values between the augmented target product and the products in the subset of products that indicate a relationship between the augmented target product and the products in the subset of products, the association values being calculated based at least in part on a comparison between the boosted historical electronic activity of the augmented target product and the historical electronic activity of the products in the subset of products; generating, by the server and for at least the augmented target product, a sorted list of products that complement the augmented target product, the sorted list of products including one or more products from the subset of products that have an association value with the augmented target product that are greater than or equal to an association value threshold; and returning, from the server and to the user interface of the user system over the network and in response to the recommendation request, product recommendations based at least in part on the sorted list of products that complement the augmented target product, the product recommendations indicating the one or more products with respective association values that satisfy the association value threshold and complement the augmented target product.
With respect to claims 8 and 15, the prior art of record, alone or combined, neither anticipates nor renders obvious an apparatus and a non-transitory machine-readable storage medium reciting similar limitations.
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 extension fee 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 date of this final action.
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/Anne M Georgalas/
Primary Examiner, Art Unit 3689