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 .
DETAILED ACTION
This is a final rejection.
Claims 1-10 are pending.
Information Disclosure Statement (IDS)
The information disclosure statement(s) filed on 02/19/2024, and 01/05/2026 comply with the provisions 37 CFR 1.97, 1.98, and MPEP 609 and is considered by the Examiner.
Status of Claims
Applicant’s response date 04/22/2026. Amending claim 1.
Election/Restriction
Applicant’s election without traverse of claims 1-10 (Group I) in the reply filed on 03/31/2025 is acknowledged.
Claims 11-20 are drawn to a nonelected invention (Group II).
The requirement is still deemed proper and it therefore made FINAL.
Response to Amendment
The previously pending rejection under 35 USC 101, will be maintained. The 101 rejection is updated in light of the amendments.
With regard to the rejection under 35 USC 103- No art rejection has been put forth in the rejection for the reason found in the “Allowable Subject Matter” section found below. Also, See applicant remarks 08/21/2025 pages 8-9.
Response to Arguments
Applicant's arguments filed 04/22/2026 have been fully considered but they are not persuasive.
Response to Arguments under 35 USC 101:
Applicant argues (Pages 10-14 of the remarks):
Applicant respectfully submits that claim 1 's 'additional elements', "inserting a virtual tracking code to downloaded versions of the target web site ... " and "using the browser native AP Is in combination with the virtual tracking code to track activity of the participants ... " improve computer functionality. The browser's native API running on a participant's data processing unit is used "in combination" with the tracking code inserted into a downloaded version of a web during the downloading of the web site to the participant's data processing unit to track a participant's activity. By using the browser's native API "in combination" with the inserted tracking code, both running on the participant's data processing unit, a participant's activity can be tracked without requiring modifying the original target web site with tracking code.
Furthermore, Applicant respectfully submits that a person of ordinary skill in the art
would understand that amended claim 1 includes the unconventional step of "using browser native AP Is in combination with the virtual tracking code to track activity of the participants ... ", in an unconventional feedback loop that includes "training the models of the plurality of models based on [the] scoring"., where "scoring each participant profile [is], based at least in part on tracked user activity ... ", which is determined using the "browser native AP Is in combination with the virtual tracking code".
Examiner respectfully disagrees:
With regard to an abstract idea, Independent Claim, when “taken as a whole,” are directed to the abstract idea and substantially recite the limitations:
A method for identifying highly ranked participants in profile clusters and performing usability resting, the method comprising:
receiving at least three features for each participant profile;
scoring each participant profile, based on tracked user activity, by quantile-based discretization;
grouping participants using an unsupervised machine learning (ML) clustering algorithm to generate a cluster from a plurality of clusters for each participant profile;
ranking the plurality of clusters based upon a model of a plurality of models, wherein each model of the plurality of models is a function of geography and study type;
sampling participants from each cluster responsive to the ranking;
inserting a virtual tracking code to downloaded versions of a target web site running on a first computer system while the target web site is being downloaded over a network to data processing units running on sampled participants' computing systems, that include browsers that run on the sampled participants' computer systems;
using the processing units at the sampled participants' computing systems to instruct the sampled participants to perform predefined tasks on the downloaded versions of the target web site;
using browser native APIs in combination with, the virtual tracking code at the sampled participants' computing systems to track activity of the participants on the version of the target web site downloaded to the data processing signals, to test the participants' user experiences; and
training the models of the plurality of models based on the scoring.
The Applicant's Specification titled "SYSTEMS AND METHODS FOR IMPROVED USER EXPERIENCE PARTICIPANT SELECTION" emphasizes the business need for data analysis, "In summary, the present disclosure relates to methods and systems for selecting participants for a user experience study. In example aspects, based on different collected data" (Spec. [0002]). Thus, data analytics to the Specification is a business concept being addressed by the claimed invention.
As the bolded claim limitations above demonstrate, independent claims 1 are directed to the abstract idea of selecting participants for a user experience study. which is considered certain methods of organizing human activity because the bolded claim limitations pertain to (i) commercial or legal interactions and (ii) managing personal behavior or relationships or interactions between people. See MPEP §2106.04(a)(2)(II).
Applicant's claims as recited above provide a business solution of sampling participants to select participants for a user experience study. Applicant's claimed invention pertains to managing personal behavior or relationships or interactions between people and including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations and because the independent claims 1 recite the abstract idea of sampling participants to select participants for a user experience study. which pertain to "social activities, teaching, and following rules or instruction" expressly categorized under managing personal behavior or relationships or interactions between people and commercial or legal interactions including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations. See MPEP §2106.04(a)(2)(II).
Furthermore, the claim limitations are also directed towards mental processes because the limitations recite scoring each participants profile by quantile-based discretization, and sampling participants to select participants for a user experience study. Which is “observation, evaluations, judgments, and opinions,” expressly categorized under mental processes. See MPEP §2106.04(a)(2)(II).
In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional element, that integrate the exception into a practical application of that exception. An “additional element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use exception, such that it is more than a drafting effort designed to monopolize the exception.
The claims recite the additional limitation an unsupervised machine learning (ML) clustering algorithm, a model of a plurality of models, code, systems, device, APIs, computer system, network, training model, and deep learning neural networks are recited in a high level of generality and recited as performing generic computer functions routinely used in computer applications. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp. 134 S. Ct, at 2360,110 USPQ2d at 1984 (see MPEP 2106.05(f).
The additional elements of a “machine learning model, deep learning neural networks, and training models”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “machine learning model, deep learning neural networks, and training models” is insufficient to show a practical application of the recited abstract idea.
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (step 2A-prong two: NO).
The Alice framework, step 2B (Part 2 of Mayo) determine if the claim is sufficient to ensure that the claim amounts to “significantly more” than the abstract idea itself. These additional elements recite conventional computer components and conventional functions of:
Independent claims do not include my limitations amounting to significantly more than the abstract idea, along. The claims include various elements that are not directed to the abstract idea. These elements include an unsupervised machine learning (ML) clustering algorithm, a model of a plurality of models, code, systems, device, APIs, computer system, network, training model, and deep learning neural networks.
Examiner asserts that an unsupervised machine learning (ML) clustering algorithm, a model of a plurality of models, code, systems, device, APIs, computer system, network, training model, and deep learning neural networks are a generic computing element performing generic computing functions. (See MPEP 2106.05(f))
Further, with regard to mining (i.e., searching over a network), receiving, processing, storing data, and parsing (i.e. extract, transform data), the courts have recognized the following computer functions as well-understood, routing, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (i.e. “receiving, processing, transmitting, storing data”, etc.) are well-understood, routine, etc. (MPEP 2106.05(d))
Therefore, the claims at issue do not require any nonconventional computer, network, or display components, or even a “non-conventional and non-generic arrangement of know, conventional pieces,” but merely call for performance of the claimed on a set of generic computer components” and display devices.
In addition, figure 1, of the specifications detail any combination of a generic computer system program to perform the method. Generically recited computer elements do not add a meaningful limitation to the abstract idea because the Alice decision noted that generic structures that merely apply abstract ideas are not significantly more than the abstract ideas.
Claim Rejections - 35 USC § 112
Claims 1-10 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claims 1, recites the limitation “using the processing units at the sampled participants' computing systems to instruct the sampled participants to perform predefined tasks on the downloaded versions of the target web site; using browser native APIs in combination with, the virtual tracking code at the sampled participants' computing systems to track activity of the participants on the version of the target web site downloaded to the data processing signals, to test the participants' user experiences; and. The specification in ¶[0042-0043] disclose, “The tracking code collects participants' activities on the downloaded web page such as the number of clicks, key strokes, keywords, scrolls, time on tasks, and the like over a period of time … participant to perform predefined tasks on the downloaded web site during a user experience test session .. ”. The specification when examined as a whole does not disclose that the system using the processing units at the sampled participants' computing systems to instruct the sampled participants to perform predefined tasks on the downloaded versions of the target web site; using browser native APIs in combination with, the virtual tracking code at the sampled participants' computing systems to track activity of the participants on the version of the target web site downloaded to the data processing signals, to test the participants' user experiences;. Examiner interpret virtual code and different version as a JavaScript that may record number of mouse click and time spent on a website.
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 1-10 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea without a practical application or significantly more than the abstract idea.
Under the 35 U.S.C. §101 subject matter eligibility two-part analysis, Step 1 addresses whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. See MPEP §2106.03. If the claim does fall within one of the statutory categories, it must then be determined in Step 2A [prong 1] whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea). See MPEP §2106.04. If the claim is directed toward a judicial exception, it must then be determined in Step 2A [prong 2] whether the judicial exception is integrated into a practical application. See MPEP §2106.04(d). Finally, if the judicial exception is not integrated into a practical application, it must additionally be determined in Step 2B whether the claim recites "significantly more" than the abstract idea. See MPEP §2106.05.
Examiner note: The Office's 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) is currently found in the Ninth Edition, Revision 10.2019 (revised June 2020) of the Manual of Patent Examination Procedure (MPEP), specifically incorporated in MPEP §2106.03 through MPEP §2106.07(c).
Regarding Step 1
Claims 1-0 are directed toward a method (process). Thus, all claims fall within one of the four statutory categories as required by Step 1.
Regarding Step 2A [prong 1]
Claims 1-10 are directed toward the judicial exception of an abstract idea.
Regarding independent claim 1, the bolded limitations emphasized below correspond to the abstract ideas of the claimed invention:
Claim 1. A method for identifying highly ranked participants in profile clusters and performing usability resting, the method comprising:
receiving at least three features for each participant profile;
scoring each participant profile, based on tracked user activity, by quantile-based discretization;
grouping participants using an unsupervised machine learning (ML) clustering algorithm to generate a cluster from a plurality of clusters for each participant profile;
ranking the plurality of clusters based upon a model of a plurality of models, wherein each model of the plurality of models is a function of geography and study type;
sampling participants from each cluster responsive to the ranking;
inserting a virtual tracking code to downloaded versions of a target web site running on a first computer system while the target web site is being downloaded over a network to data processing units running on sampled participants' computing systems, that include browsers that run on the sampled participants' computer systems;
using the processing units at the sampled participants' computing systems to instruct the sampled participants to perform predefined tasks on the downloaded versions of the target web site;
using browser native APIs in combination with, the virtual tracking code at the sampled participants' computing systems to track activity of the participants on the version of the target web site downloaded to the data processing signals, to test the participants' user experiences; and
training the models of the plurality of models based on the scoring.
The Applicant's Specification titled "SYSTEMS AND METHODS FOR IMPROVED USER EXPERIENCE PARTICIPANT SELECTION" emphasizes the business need for data analysis, "In summary, the present disclosure relates to methods and systems for selecting participants for a user experience study. In example aspects, based on different collected data" (Spec. [0002]). Thus, data analytics to the Specification is a business concept being addressed by the claimed invention.
As the bolded claim limitations above demonstrate, independent claims 1 are directed to the abstract idea of selecting participants for a user experience study. which is considered certain methods of organizing human activity because the bolded claim limitations pertain to (i) commercial or legal interactions and (ii) managing personal behavior or relationships or interactions between people. See MPEP §2106.04(a)(2)(II).
Applicant's claims as recited above provide a business solution of sampling participants to select participants for a user experience study. Applicant's claimed invention pertains to managing personal behavior or relationships or interactions between people and including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations and because the independent claims 1 recite the abstract idea of sampling participants to select participants for a user experience study. which pertain to "social activities, teaching, and following rules or instruction" expressly categorized under managing personal behavior or relationships or interactions between people and commercial or legal interactions including agreements in the form of contracts, legal obligations; advertising, marketing or sales activities or behaviors; business relations. See MPEP §2106.04(a)(2)(II).
Furthermore, the claim limitations are also directed towards mental processes because the limitations recite scoring each participants profile by quantile-based discretization, and sampling participants to select participants for a user experience study. Which is “observation, evaluations, judgments, and opinions,” expressly categorized under mental processes. See MPEP §2106.04(a)(2)(II).
Dependent claims 2-10 further reiterate the same abstract ideas with further embellishments (the bolded limitations), such as
claim 2 wherein the scores include: 1) time since last participation, 2) total number of participations of the given participant profile, 3) time response score,4) quality response score, 5) burnout ratio, and 6) exclusion variable.
claim 3 wherein each cluster has a single score for each model.
claim 4 further comprising receiving a numerical weight for each of the scores.
claim 5 wherein each participant profile is assigned to a single cluster for each model of the plurality of models.
claim 6 wherein the sampling proportion from each cluster is correlated with the cluster score.
claim 7 wherein the sampling includes ponderation from lower ranked clusters.
claim 8 further comprising clustering new participant profiles using supervised modeling.
claim 9 further comprising intentionally sending an invitation to the selected participants which are a better fit to engage in a user experience study.
Claim 10 further comprising asking the filtered participants at least one question to determine at least one missing feature.
which are nonetheless directed towards fundamentally the same abstract ideas as indicated for independent claim 1.
Regarding Step 2A [prong 2]
Claims 1-10 fail to integrate the abstract idea into a practical application. Independent claim 1 include the following bolded additional elements which do not amount to a practical application:
Claim 1. an unsupervised machine learning (ML) clustering algorithm
a model of a plurality of models, wherein each model of the plurality of models, code, systems, device and deep learning neural networks, APIs, computer system, network, training model
The bolded limitations recited above in independent claim 1 pertain to additional elements which merely provide an abstract-idea-based-solution implemented with computer hardware and software components, including the additional elements of an unsupervised machine learning (ML) clustering algorithm, APIs, computer system, network, training model, a model of a plurality of models, code, systems, device and deep learning neural networks. which fail to integrate the abstract idea into a practical application because there are (1) no actual improvements to the functioning of a computer, (2) nor to any other technology or technical field, (3) nor do the claims apply the judicial exception with, or by use of, a particular machine, (4) nor do the claims provide a transformation or reduction of a particular article to a different state or thing, (5) nor provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of MPEP §2106.04(d)(1) and §2106.05 (a-c & e-h), (6) nor do the claims apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, in view of MPEP §2106.04(d)(2).
The Specification provides a high level of generality regarding the additional elements claimed without sufficient detail or specific implementation structure so as to limit the abstract idea, for instance, the computing platform includes generic processors, memories, and communication interfaces. Paragraph [figure 4] of the specification. Nothing in the Specification describes the specific operations recited in claim 1 as particularly invoking any inventive programming, or requiring any specialized computer hardware or other inventive computer components, i.e., a particular machine, or that the claimed invention is somehow implemented using any specialized element other than all-purpose computer components to perform recited computer functions. The claimed invention is merely directed to utilizing computer technology as a tool for solving a business problem of data analytics. Nowhere in the Specification does the Applicant emphasize additional hardware and/or software elements which provide an actual improvement in computer functionality, or to a technology or technical field, other than using these elements as a computational tool to automate and perform the abstract idea. See MPEP §2106.05(a & e).
The additional elements of a “an unsupervised machine learning (ML) clustering algorithm, a model of a plurality of models, and deep learning neural networks, and training models”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “an unsupervised machine learning (ML) clustering algorithm, a model of a plurality of models and deep learning neural networks, and training models ” is insufficient to show a practical application of the recited abstract idea.
The relevant question under Step 2A [prong 2] is not whether the claimed invention itself is a practical application, instead, the question is whether the claimed invention includes additional elements beyond the judicial exception that integrate the judicial exception into a practical application by imposing a meaningful limit on the judicial exception. This is not the case with Applicant's claimed invention which merely pertains to steps for scoring each participants profile by quantile-based discretization, and sampling participants to select participants for a user experience study and the additional computer elements a tool to perform the abstract idea, and merely linking the use of the abstract idea to a particular technological environment. See MPEP §2106.04 and §21062106.05(f-h). Alternatively, the Office has long considered data gathering, analysis and data output to be insignificant extra-solution activity, and these additional elements do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.04 and §2106.05(g). Thus, the additional elements recited above fail to provide an actual improvement in computer functionality, or to a technology or technical field. See MPEP §2106.04(d)(1) and §2106§2106.05 (a & e).
Instead, the recited additional elements above, merely limit the invention to a technological environment in which the abstract concept identified above is implemented utilizing the computational tools provided by the additional elements to automate and perform the abstract idea, which is insufficient to provide a practical application since the additional elements do no more than generally link the use of the abstract idea to a particular technological environment. See MPEP §2106.04. Automating the recited claimed features as a combination of computer instructions implemented by computer hardware and/or software elements as recited above does not qualify an otherwise unpatentable abstract idea as patent eligible. Alternatively, the Office has long considered data gathering and data processing as well as data output recruitment information on a social network to be insignificant extra-solution activity, and these additional elements used to gather and output recruitment information on a social network are insignificant extra-solution limitations that do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.05(g). The current invention directed to scoring each participants profile by quantile-based discretization, and sampling participants to select participants for a user experience study. When considered in combination, the claims do not amount to improvements of the functioning of a computer, or to any technology or technical field. Applicant's limitations as recited above do nothing more than supplement the abstract idea using additional hardware/software computer components as a tool to perform the abstract idea and generally link the use of the abstract idea to a technological environment, which is not sufficient to integrate the judicial exception into a practical application since they do not impose any meaningful limits.
Dependent claims 2-10 merely incorporate the additional elements recited above, along with further embellishments of the abstract idea of independent claim 1 respectively, for example, the bolded limitations emphasized below correspond to the additional elements: claim 8 “supervised modeling”. This limitation is at most merely insignificant extra-solution activity (MPEP 2106.05(g)) and thus fails to integrate the recited abstract idea into a practical application. This limitation is at most merely insignificant extra-solution activity (MPEP 2106.05(g)) and thus fails to integrate the recited abstract idea into a practical application. Which are nonetheless directed towards fundamentally the same abstract ideas as indicated for independent claim 1, but these features only serve to further limit the abstract idea of independent claim 1, furthermore, merely using/applying in a computer environment such as merely using the computer as a tool to apply instructions of the abstract idea do nothing more than provide insignificant extra-solution activity since they amount to data gathering, analysis and outputting. Furthermore, they do not pertain to a technological problem being solved in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, and/or the limitations fail to achieve an actual improvement in computer functionality or improvement in specific technology other than using the computer as a tool to perform the abstract idea.
Therefore, the additional elements recited in the claimed invention individually, and in combination fail to integrate the recited judicial exception into any practical application.
Regarding Step 2B
Claims 1-10 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element(s) as described above with respect to Step 2A Prong 2, the additional element of Claim 1. an unsupervised machine learning (ML) clustering algorithm, a model of a plurality of models, code, systems, device, APIs, computer system, network, training model and deep learning neural networks. The displaying interface and storing data merely amount to a general purpose computer used to apply the abstract idea(s) (MPEP 2106.05(f)) and/or performs insignificant extra-solution activity, e.g. data retrieval and storage, as described above (MPEP 2106.05(g)) which are further merely well-understood, routine, and conventional activit(ies) as evidenced by MPEP 2106.06(05)(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, electronically scanning or extracting data from a physical document, and a web browser’s back and forward button functionality). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that the claims amount to significantly more than the abstract idea directed to scoring each participants profile by quantile-based discretization, and sampling participants to select participants for a user experience study.
Claims 1-10 is accordingly rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea(s)) without significantly more.
Allowable Subject Matter
Regarding the 35 USC 103 rejection, No art rejections has been put forth in the rejection.
Closest prior art to the invention include Mestres US 2021/0019213: Systems and methods for the analysis of user experience testing with AI acceleration, and Seufert, Michael. "Statistical methods and models based on quality of experience distributions." Quality and User Experience 6.1 (2021): 3..
None of the prior art of record, taken individually or in combination, teach, inter alia, teaches the claimed invention as detailed in independent claims, scoring each participant profile by quantile-based discretization;
the grouping participants using an unsupervised machine learning (ML) clustering algorithm to generate a cluster from a plurality of clusters for each participant profile;
ranking the plurality of clusters based upon a model of a plurality of models, wherein each model of the plurality of models is a function of geography and study type”. The reason for not applying a rejection under 35 USC 102/103 of claims 1-10 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
DI CITTADINANZA IR. ALMA MATER STUDIORUM–UNIVERSITA’DI BOLOGNA. 2018
Kim et al. US 2020/0090059: Utilizing machine learning models to automatically generate contextual insights and actions based on legal regulations.
Wadhwa et al. US 2021/0357869: Instant content notification with user similarity.
Zenine WO2022/018505: method for near-real-time communicating negative user experience of users interacting with a website.
Dalal et al. US 2009/0292584: System and method for context and community based customization for a user experience.
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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/HAMZEH OBAID/Primary Examiner, Art Unit 3624
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