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 .
Notice to Applicant
Claims 1-2, 11-12 and 20 are presently amended.
Claims 10 and 19 are cancelled.
Claims 1-9, 11-18 and 20 are pending.
Response to Amendment
Applicant’s amendments are acknowledged.
Response to Arguments
Applicant' s arguments filed 4/15/2026 have been fully considered in view of further consideration of statutory law, Office policy, precedential common law, and the cited prior art as necessitated by the amendments to the claims, and are persuasive in-part for the reasons set forth below.
35 USC § 101 Rejections
First, Applicant argues that “…the amended claims recite eligible subject matter… The Examiner has characterized the claims as being directed to collecting, analyzing, and using data for targeted advertising. Applicant respectfully submits that this characterization is an overgeneralization that fails to consider the claim as a whole. Claim 1, as amended, recites a specific computer-implemented method performed by a user segmentation system operating in conjunction with one or more communication devices via a communication network, and therefore cannot be reduced to a mere abstract idea.
Amended claim 1 explicitly requires that a plurality of users is associated with one or more communication devices and that live event data is obtained based on activities performed by the users on the communication devices… This reflects a multi-source data acquisition mechanism involving multiple system components, which cannot be practically performed in the human mind…
This real-time constraint imposes a requirement of continuous system operation and coordinated execution across multiple components, which cannot be performed mentally…
Accordingly, when considered as a whole, amended claim 1 is directed to a network- based, real-time system involving interaction between a user segmentation system and communication devices, and do not recite a judicial exception under Step 2A, Prong 1…” [Arguments, pages 19-22].
In response, Applicant’s arguments are considered but are not persuasive. Examiner respectfully disagrees and maintains that the presently amended claims recite an abstract idea. In particular, when considered as a whole, Examiner maintains that the present invention generally describes a method and system for creating market segments and initializing marketing campaigns. The elements including the communication devices and real-time constraints cited in the above-argument do not change the general thrust of the invention. Thus, when considered as a whole, the present claims and limitations describe steps for commercial or legal interactions, which includes agreements in the form of contracts; legal obligations; advertising, and marketing or sales activities or behaviors; business relations. Specifically, creating market segments and initializing marketing campaigns is considered to describe marketing activities and behaviors. Examiner therefore respectfully maintains that claims 1, 11 and 20 recite concepts identified as abstract ideas, namely certain methods of organizing human activity. As such, Examiner remains unpersuaded.
Second, Applicant argues that “…amended independent claims 1, 11, and 20 nevertheless satisfy prong two of Step 2A analysis… The specification identifies deficiencies in prior systems, including the inability to perform segmentation at a granular level in real-time… Amended claim 1 addresses these deficiencies by requiring that the user segmentation system obtains live event data corresponding to user activities on communication devices…
Amended claim 1 defines a closed-loop operational mechanism in which user activity on communication devices is captured, processed by the user segmentation system, and used to control subsequent system behavior through transmission of advertisements…
The requirement that advertisements are transmitted to communication devices for real-time display demonstrates that the claimed method results in a tangible system-level action that affects the operation of communication devices. The suggestion that such transmission constitutes insignificant extra-solution activity is not consistent with the claim language… This loop is enabled through the communication network and operates in real- time. The Examiner's analysis does not address this closed-loop interaction and instead isolates only the data analysis portion of the claim…
Moreover, amended claim 1 imposes meaningful limitations by specifying particular data sources, behavioral categorization into past and live activities, application of filters, and real-time transmission of output. These limitations tie the claimed method to a specific implementation within a technological environment. The assertion that the claims are implemented on a generic computer overlooks the recited interaction between the user segmentation system, communication devices, and communication network… [Arguments, pages 22-25].
In response, Applicant’s arguments are considered but are not persuasive. Examiner respectfully disagrees and maintains that the presently amended claims recite an abstract idea without significantly more. In particular, Examiner first observes that the claims do not appear to recite more than a drafting effort designed to monopolize the judicial exception. For example, claim 1 recites language including, “…wherein the first set of data is received from a plurality of data sources including one or more online platform databases, communication device databases, and third-party databases…” and “…wherein the analysis is performed based on training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…” (Claim 1).
Examiner observes that the claims, when considered as a whole and in light of the recited additional elements, do not impose meaningful limits on the data being analyzed. Examiner observes that the claimed data events and patterns appear to be drafted to claim large portions of marketing activities, including data related to online shopping and banking, holiday plans, properties bought, stock investments, hospital visits, videos watched, personal trainers hired, etc.
Similarly, the claims and additional elements do not impose meaningful limits on the ways that the data are stored or analyzed. For example, as reproduced above, the data can be received from one or more of …online platform databases, communication device databases, and third-party databases, and analyzed with either a supervised or an unsupervised model. Further still, simply claiming that the processes are performed in a closed loop and in real-time is not considered sufficient to demonstrate a meaningful limit on the claimed invention. Thus, Examiner respectfully maintains that the claimed additional elements amount to mere instructions to apply an exception (See MPEP 2106.05(f)). As such, Examiner remains unpersuaded.
Third, Applicant argues that “Additional elements recited in the claims provide significantly more than an abstract idea because the additional elements are unconventional in combination…
The Examiner's analysis improperly considers the claim elements individually and concludes that each element is conventional…
Amended claim 1 defines a specific ordered combination that includes receiving data from multiple defined sources, obtaining real-time live event data from communication devices, analyzing the data using machine learning, creating segments based on defined behavioral categories, identifying patterns using filters, triggering campaigns, and transmitting advertisements to communication devices via a communication network for real-time display.
It is not shown that this specific combination, particularly the integration of real-time processing with network-based transmission, is well-understood, routine, or conventional… The assertion that the claims merely apply generic computer functions does not account for this coordinated real-time operation.
The transmission of advertisements to communication devices via a communication network is an integral part of the claimed method and creates a functional relationship between the processing steps and the system output. The results of the analysis are not merely displayed but are used to control what is transmitted and displayed on user devices. This demonstrates that the claims are directed to a functional system implementation, rather than a mere abstract idea.
The claimed invention also improves system functionality by enabling real-time responsiveness to user activity, which is identified in the specification as a deficiency in prior systems. The Office Action do not address this improvement and do not provide evidence that such real-time coordinated operation across multiple components is conventional.
Finally, amended claim 1 is narrowly tailored to a specific configuration involving defined data sources, behavioural categories, filtering mechanisms, and network-based transmission. The claims therefore do not pre-empt all forms of user segmentation or advertising. The Examiner's broad characterization does not reflect the actual scope of the claims…” [Arguments, pages 25-28].
In response, Applicant’s arguments are considered but are not persuasive. Examiner respectfully disagrees and maintains that the presently amended claims recite an abstract idea. In particular, and with respect to the argument that it is not shown that the integration of real-time processing with network-based transmission, is well-understood, routine, or conventional, Examiner respectfully disagrees and observes that appropriate forms of support include one or more of the following: (a) A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s); (b) A citation to one or more of the court decisions discussed in Subsection II below as noting the well-understood, routine, conventional nature of the additional element(s); (c) A citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and (d) A statement that the examiner is taking official notice of the well-understood, routine, conventional nature of the additional element(s).
Examiner observes that the previous Office Action found that the claimed additional elements including the system, devices, machine learning model and executable instructions are recited at a high-level of generality (see MPEP § 2106.05(a)), like the following MPEP example:
iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48
Furthermore, the computer implemented element is considered to amount to no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)), like the following MPEP example:
i. A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015);
Accordingly, the well-understood, routine, or conventional analysis has been satisfied by citation to one or more of the court decisions discussed in Subsection II of 2106.05(d) as noting the well-understood, routine, conventional nature of the additional elements.
Further, Examiner observes that the present specification states the following:
“each of the one or more communication devices 204 perform computing operations based on any suitable operating system… the mobile operating system includes but may not be limited to windows operating system, android operating system, iOS operating system, symbian operating system, bada operating system from Samsung Electronics and BlackBerry operating system, and sailfish…” (Specification, ¶ 62).
“In an example, the operating system installed inside the one or more communication devices 204 is windows. In another example, the operating system installed inside the one or more communication devices 204 is Mac. In yet another example, the operating system installed inside the one or more communication devices 204 is Linux based operating system. In yet another example, the operating system installed inside the one or more communication devices 204 is Chrome OS. In yet another example, the operating system installed inside the one or more communication devices 204 may be one of UNIX, Kali Linux, and the like. …” (Specification, ¶ 63).
“The computing device 2600 typically includes a variety of computer-readable media. The computer-readable media can be any available media that can be accessed by the computing device 2600 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, the computer-readable media may comprise computer storage media and communication media. The computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data.” (Specification, ¶ 167).
Examiner observes that the specification states that the system can be performed on virtually any existing operating system and through the use of any type of computer memory. Examiner observes that the all-encompassing and non-specific nature of these elements fails to demonstrate anything other than well-understood, routine, conventional operations. Thus, Examiner respectfully maintains that the additional elements fail to amount to an inventive concept that is significantly more than an abstract idea here, in Step 2B. As such, Examiner remains unpersuaded.
Claim Rejections - 35 USC § 101
Claims 1-9, 11-18 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: Claims 1-9, 11-18 and 20 are directed to statutory categories, namely a process (claims 1-9), a machine (claims 11-18) and an article of manufacture (claim 20).
Step 2A, Prong 1: Claims 1, 11 and 20 in part, recite the following abstract idea:
…receiving, at… a first set of data associated with a plurality of users, wherein the plurality of users is associated with… wherein the first set of data is received from a plurality of data sources including … in real time; fetching, at…, a second set of data associated with a plurality of past events of the plurality of users on…; obtaining, at… a third set of data associated with a plurality of live events of the plurality of users on… wherein the third set of data is obtained in real-time; analyzing, at… the first set of data, the second set of data and the third set of data…, wherein the analysis is performed based on… wherein the analysis is performed to identify one or more behavioral patterns from the first set of data, the second set of data, and the third set of data for a past behavior category and a live behavior category, wherein the analysis is performed in real time, wherein the behavioral patterns comprise uniform resource locater visit pattern, webpage visit pattern, number of webpage accessed pattern, application installation pattern, application launch pattern, application uninstallation pattern, accessed content pattern, started content pattern, paused content pattern, resumed content pattern, searched content pattern, notification click pattern, notification views pattern; creating, in real time at… one or more segments of the plurality of users based on the analysis of the first set of data, the second set of data, and the third set of data, the past behavior category, and the live behavior category, wherein the past behavior category includes a plurality of first sub-categories including a past action sub-category, a past inaction sub-category, and a past action with properties sub-category, wherein the past action sub-category includes the plurality of past events, and a plurality of parameters including a day, a time, a language, a location, one or more events, an inactivity, and an online platform, wherein the past inaction sub-category includes a plurality of past inactions that are not performed by the plurality of users, wherein the past action with properties sub-category includes a plurality of properties including user properties, demographic properties, geographic properties, technographic properties, reachability, and application fields, wherein the live behavior category includes a plurality of second sub-categories including a real-time action sub-category, a real- time inaction sub-category, a real-time page visit sub-category, and a real-time page count sub- category, wherein the real-time action sub-category includes the plurality of live events, wherein the real-time inaction sub-category includes a plurality of live inactions corresponding to live events that are not performed by the plurality users within a pre-defined time, and wherein each of the past inaction sub-category, the past action with properties sub-category, the real-time action sub-category, and real-time inaction sub-category includes the plurality of parameters; identifying … one or more patterns of the one or more segments using a plurality of filters, wherein the plurality of filters is based on one or more parameters; generating, at the user segmentation system with the processor, a segment trend plot for each of the one or more segments based on the one or more identified patterns of the one or more segments, wherein the segment trend plot is generated in one or more graphical forms downloadable in one or more formats; triggering, in real time at… initialization of one or more marketing campaigns for a subset or an entirety of users in the one or more segments based on the generated segment trend plot of the one or more segments, wherein the subset or the entirety of users in the one or more segments of the plurality of users meets a criteria for initializing the one or more marketing campaigns, wherein the one or more marketing campaigns comprises one or more advertiser defined parameters, wherein the advertiser defined parameters include one or more of minimum spend, discounts, campaign duration, campaign relevancy, campaign location, a customer's patronage of the online platform, or user interaction; and transmitting by… one or more advertisements associated with the one or more marketing campaigns for the subset or the entirety of users in the one or more segments of the plurality of users …for display in real-time, based on the triggering of the initialization of the one or more marketing campaigns and the one or more patterns, wherein the one or more advertisements are displayed to each user among the subset or the entirety of users in the one or more segments of the plurality of users on their associated … in real-time [Claim 1],
…perform a method for granular level segmentation of users based on activities on online platforms in real-time, the method comprising: receive, at…, a first set of data associated with a plurality of users, wherein the plurality of users is associated with …, wherein the first set of data is received from a plurality of data sources including… in real time; fetch, at …, a second set of data associated with a plurality of past events of the plurality of users …; obtain, at …, a third set of data associated with a plurality of live events of the plurality of users …, wherein the third set of data is obtained in real-time; analyze, …, the first set of data, the second set of data and the third set of data …, wherein the analysis is performed based on …, wherein the analysis is performed to identify one or more behavioral patterns from the first set of data, the second set of data, and the third set of data for a past behavior category and a live behavior category, wherein the analysis is performed in real time, wherein the behavioral patterns comprise uniform resource locater visit pattern, webpage visit pattern, number of webpage accessed pattern, application installation pattern, application launch pattern, application uninstallation pattern, accessed content pattern, started content pattern, paused content pattern, resumed content pattern, searched content pattern, notification click pattern, notification views pattern; create, in real time at… one or more segments of the plurality of users based on the analysis of the first set of data, the second set of data, and the third set of data, the past behavior category and the live behavior category, wherein the past behavior category includes a plurality of first sub-categories including a past action sub- category, a past inaction sub-category, and a past action with properties sub- category, wherein the past action sub-category includes the plurality of past events, and a plurality of parameters including a day, a time, a language, a location, one or more events, an inactivity, and an online platform, wherein the past inaction sub-category includes a plurality of past inactions that are not performed by the plurality of users, wherein the past action with properties sub- category includes a plurality of properties including user properties, demographic properties, geographic properties, technographic properties, reachability, and application fields, wherein the live behavior category includes a plurality of second sub-categories including a real-time action sub-category, a real-time inaction sub-category, areal-time page visit sub-category, and a real-time page count sub- category, wherein the real-time action sub-category includes the plurality of live events, wherein the real-time inaction sub-category includes a plurality of live inactions corresponding to live events that are not performed by the plurality users within a pre-defined time, and wherein each of the past inaction sub-category, the past action with properties sub-category, the real-time action sub-category, and real-time inaction sub-category includes the plurality of parameters; identify, … one or more patterns of the one or more segments using a plurality of filters, wherein the plurality of filters is based on one or more parameters, wherein the one or more segments are created in real-time; generate, … a segment trend plot for each of the one or more segments based on the one or more identified patterns of the one or more segments, wherein the segment trend plot is generated in one or more graphical forms downloadable in one or more formats; trigger, in real time at… initialization of one or more marketing campaigns for a subset or an entirety of users in the one or more segments based on the generated segment trend plot of the one or more segments, wherein the subset or the entirety of users in the one or more segments of the plurality of users meets a criteria for initializing the one or more marketing campaigns, wherein the one or more marketing campaigns comprises one or more advertiser defined parameters, wherein the advertiser defined parameters include one or more of minimum spend, discounts, campaign duration, campaign relevancy, campaign location, a customer's patronage of the online platform, or user interaction; and transmit by … one or more advertisements associated with the one or more marketing campaigns for the subset or the entirety of users in the one or more segments of the plurality of users …for display in real-time, based on the triggering of the initialization of the one or more marketing campaigns and the one or more patterns, wherein the one or more advertisements are displayed to each user among the subset or the entirety of users in the one or more segments of the plurality of users on their associated … in real-time. [Claim 11],
…receiving, … a first set of data associated with a plurality of users, wherein the plurality of users is associated with… wherein the first set of data is received from a plurality of data sources including… in real time; fetching, at… a second set of data associated with a plurality of past events of the plurality of users… ; obtaining, at…, a third set of data associated with a plurality of live events of the plurality of users on…, wherein the third set of data is obtained in real-time; analyzing, … the first set of data, the second set of data and the third set of data… wherein the analysis is performed based on wherein the analysis is performed to identify one or more behavioral patterns from the first set of data, the second set of data, and the third set of data for a past behavior category and a live behavior category, wherein the analysis is performed in real time, wherein the behavioral patterns comprise uniform resource locater visit pattern, webpage visit pattern, number of webpage accessed pattern, application installation pattern, application launch pattern, application uninstallation pattern, accessed content pattern, started content pattern, paused content pattern, resumed content pattern, searched content pattern, notification click pattern, notification views pattern; creating, in real time at… one or more segments of the plurality of users based on the analysis of the first set of data, the second set of data, and the third set of data, the past behavior category, and the live behavior category, wherein the past behavior category includes a plurality of first sub- categories including a past action sub-category, a past inaction sub-category, and a past action with properties sub-category, wherein the past action sub-category includes the plurality of past events, and a plurality of parameters including a day, a time, a language, a location, one or more events, an inactivity, and an online platform, wherein the past inaction sub-category includes a plurality of past inactions that are not performed by the plurality of users, wherein the past action with properties sub- category includes a plurality of properties including user properties, demographic properties, geographic properties, technographic properties, reachability, and application fields, wherein the live behavior category includes a plurality of second sub-categories including a real-time action sub-category, a real-time inaction sub- category, a real-time page visit sub-category, and a real-time page count sub- category, wherein the real-time action sub-category includes the plurality of live events, wherein the real-time inaction sub-category includes a plurality of live inactions corresponding to live events that are not performed by the plurality users within a pre-defined time, and wherein each of the past inaction sub-category, the past action with properties sub-category, the real-time action sub-category, and real-time inaction sub-category includes the plurality of parameters; identifying, … one or more patterns of the one or more segments using a plurality of filters, wherein the plurality of filters is based on one or more parameters; generating … a segment trend plot for each of the one or more segments based on the one or more identified patterns of the one or more segments, wherein the segment trend plot is generated in one or more graphical forms downloadable in one or more formats; triggering, in real time at… initialization of one or more marketing campaigns for a subset or an entirety of users in the one or more segments based on the generated segment trend plot of the one or more segments, wherein the fourth set of data of the subset or the entirety of users in the one or more segments of the plurality of users meets a criteria for initializing the one or more marketing campaigns, wherein the one or more marketing campaigns comprises one or more advertiser defined parameters, wherein the advertiser defined parameters include one or more of minimum spend, discounts, campaign duration, campaign relevancy, campaign location, a customer's patronage of the online platform, or user interaction; and transmitting …, one or more advertisements associated with the one or more marketing campaigns for the subset or the entirety of users in the one or more segments of the plurality of users …for display in real-time, based on the triggering of the initialization of the one or more marketing campaigns and the one or more patterns, wherein the one or more advertisements are displayed to each user among the subset or the entirety of users in the one or more segments of the plurality of users on their associated … in real-time. [Claim 20].
These concepts are not meaningfully different than the following concepts identified by the MPEP:
Concepts relating to certain methods of organizing human activity. The aforementioned limitations describe steps for commercial or legal interactions, which includes agreements in the form of contracts; legal obligations; advertising, and marketing or sales activities or behaviors; business relations). Specifically, creating market segments and initializing marketing campaigns is considered to describe marketing activities and behaviors. As such, claims 1, 11 and 20 recite concepts identified as abstract ideas.
The dependent claims recite limitations relative to the independent claims, including, for example:
…wherein the first set of data corresponds to personal information of the plurality of users, wherein the first set of data comprises name data, age data, e-mail identity data, contact number data, gender data, geographic location data, angiographic data, demographic data, payment cards data, banking partners data, and relationship status data [Claims 2 and 12],
… wherein the second set of data corresponds the plurality of past events of the plurality of users, wherein the plurality of past events comprises past uniform resource locater visits, past number of visits, past number of pages accessed, past webpage visited, past application installed, past number of times application installed, past application launched, past number of times application launched, past application uninstalled, past accessed content, past started content, past paused content, past resumed content, past searched content, past notification clicks, past notification views, past products surfed, past products added to cart, past reviews for products, past favorite product category, past inactivity for products, past accounts opened, past credit card requests, past credit cards issued, past loan requests, past net- banking requests, past multimedia content surfed, past multimedia content watched, past texts exchanged, past business blogs, past live media streamed, past audio-video callings, past medicines searched, past medicines bought, past medical test kit bought, past medical tests scheduled, past bill payments, past doctor consultation scheduled, past hospital visit planned… [Claims 3 and 13],
…wherein the third set of data corresponds the plurality of live events of the plurality of users, wherein the plurality of live events comprises real-time uniform resource locater visits, real-time number of webpage visits, real-time number of webpages accessed, real-time webpage visit, real- time application installed, real-time application launch, real-time application uninstalled, real- time accessed content, real-time started content, real-time paused content, real-time resumed content, real-time searched content, real-time notification clicks, real-time notification views, real-time products surfed, real-time products added to cart, real-time reviews for products, real-time favorite product category, real-time inactivity for products, real- time accounts opened, real-time credit card requests, real-time credit cards issued, real-time loan requests, real-time net-banking requests, real-time multimedia content surfed, real-time multimedia content watched, real-time texts exchanged, real-time business blogs, real-time live media streamed, real-time audio-video callings, real-time medicines searched, real-time medicines bought, real-time medical test kit bought, real-time medical tests scheduled, real- time bill payments, real-time doctor consultation scheduled, real-time hospital visit planned, real-time dietary plan requested, real-time personal trainer hired, real-time fitness center searched, real-time educational video searched, real-time educational video watched, real- time projects submitted, real-time mock tests subscribed, real-time educational counselling requested, real-time problem solving session requested, real-time international masters interests, real-time properties searched, real-time properties watched, real-time properties… [Claims 4 and 14],
…wherein the past behavior category and the live behavior category are pre-defined by an administrator [Claims 6 and 15],
…wherein the one or more behavioral patterns further comprise products surfed pattern, products added to cart pattern, reviews for products pattern, favorite product category pattern, inactivity for products pattern, accounts opened pattern, credit card requests pattern, credit cards issued pattern, loan request patterns, net-banking requests pattern, multimedia content surfed pattern, multimedia content watched pattern, texts exchanged pattern, business blogs pattern, live media streamed pattern, audio-video calling pattern, medicines searched pattern, medicines bought pattern, medical test kit bought pattern, medical tests scheduled pattern, bill payments pattern, doctor consultation scheduled pattern, hospital visit pattern, dietary plan request pattern, personal trainer hired pattern, fitness center search pattern, educational video search pattern, educational video watched pattern, projects submission pattern, mock tests subscription pattern, educational counselling request pattern, problem solving session request pattern, international masters interests pattern, properties search pattern, properties watched pattern, properties bought pattern, rented properties search pattern, maintenance services request pattern, hotel search pattern, hotels added to watch-list pattern, hotel bookings pattern, holiday plans search pattern, holiday plans booked pattern, stock exchange investments pattern, money donated pattern, inactivity for product category pattern, account creation pattern, products bought pattern, repeated products pattern, subscriptions pattern, subscription renewals pattern, subscription skipped pattern, initiated transactions pattern, failed transactions pattern, content added to cart pattern, completed transactions pattern, most visited category pattern, content details watched pattern, video on demand accessed pattern, video on demand initiated pattern, and video on demand searched pattern, wherein the past behavior category allows the segmentation of the plurality of users based on the plurality of past events, wherein the live behavior category allows the segmentation of the plurality of users based on the plurality of live events [Claims 7 and 16],
…wherein the plurality of filters comprises time based filters, days based filters, age based filters, location based filters, events based filters, inactivity based filters, user properties filters, demographic filters, geographic filters, technographic filters, and application field filters, wherein the one or more parameters comprise day, time, language, location, events, inactivity, and online platform [Claims 8 and 17],
…wherein the one or more graphical forms comprise bar graph, histogram, pictogram, pie graph, line graph, and cartesian graph, and wherein the one or more formats comprise chart, joint photographic experts' group, portable network graphics, portable document format, scalable vector graphics, and comma-separated values [Claims 9 and 18].
The limitations of these dependent claims are merely narrowing the abstract idea identified in the independent claims, and thus, the dependent claims also recite abstract ideas.
Step 2A, Prong 2: This judicial exception is not integrated into a practical application. In particular, claims 1, 11 and 20 only recite the following additional elements –
…a user segmentation system with a processor… one or more communication devices… one or more online platform databases, communication device databases, and third-party databases…; … the user segmentation system with the processor… one or more online platforms through the one or more communication devices; …the user segmentation system with the processor…; …the user segmentation system with the processor…; …an operating system of the one or more communication devices…; …the one or more communication devices…; …the one or more online platforms through the one or more communication devices… the user segmentation system with the processor; … using one or more machine learning algorithms… training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…; … the user segmentation system with the processor…; …the user segmentation system with the processor…; …at the user segmentation system with the processor… …to the one or more communication devices… one or more communication devices… [Claim 1],
…one or more processors; and a memory coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, cause the one or more processors to…; …a user segmentation system with a processor… one or more communication devices… one or more online platform databases, communication device databases, and third-party databases…; … the user segmentation system with the processor… one or more online platforms through the one or more communication devices; …the user segmentation system with the processor…; the user segmentation system with the processor…; …an operating system of the one or more communication devices…; …the one or more communication devices…; …the one or more online platforms through the one or more communication devices… the user segmentation system with the processor; … using one or more machine learning algorithms… training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…; … the user segmentation system with the processor…; …the user segmentation system with the processor…; …at the user segmentation system with the processor… …to the one or more communication devices… one or more communication devices… [Claim 11],
…at a computing device… one or more communication devices…; …the computing device… on one or more online platforms through the one or more communication devices… one or more online platform databases, communication device databases, and third-party databases…; the user segmentation system with the processor…; …an operating system of the one or more communication devices…; …the one or more communication devices…; … the computing device… the one or more online platforms through the one or more communication devices…; … at the computing device… ; … using one or more machine learning algorithms… training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…; … at the computing device… at the computing device…; …at the user segmentation system with the processor… to the one or more communication devices… one or more communication devices… [Claim 20].
The dependent claims recite the following new additional elements –
…wherein the more online platforms comprise an over-the top media platform, an e-commerce platform, a fintech platform, a social media platform, a health platform, an educational platform, a real estate and housing platform, and a travel platform [Claim 5].
The system, devices, machine learning model and executable instructions are recited at a high-level of generality (see MPEP § 2106.05(a)), like the following MPEP example:
iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48
Furthermore, the computer implemented element is considered to amount to no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)), like the following MPEP example:
i. A commonplace business method or mathematical algorithm being applied on a general purpose computer, Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015);
Accordingly, these additional elements do not integrate the abstract idea into a practical application.
The remaining dependent claims do not recite any new additional elements, and thus do not integrate the abstract idea into a practical application.
Step 2B: Claims 1, 11 and 20 and their underlying limitations, steps, features and terms, considered both individually and as a whole, do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the following reasons:
…a user segmentation system with a processor… one or more communication devices… one or more online platform databases, communication device databases, and third-party databases…; … the user segmentation system with the processor… one or more online platforms through the one or more communication devices; …the user segmentation system with the processor…; …the user segmentation system with the processor…; …an operating system of the one or more communication devices…; …the one or more communication devices…; …the one or more online platforms through the one or more communication devices… the user segmentation system with the processor; … using one or more machine learning algorithms… training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…; … the user segmentation system with the processor…; …the user segmentation system with the processor…; …at the user segmentation system with the processor… …to the one or more communication devices… one or more communication devices… [Claim 1],
…one or more processors; and a memory coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, cause the one or more processors to…; …a user segmentation system with a processor… one or more communication devices… one or more online platform databases, communication device databases, and third-party databases…; … the user segmentation system with the processor… one or more online platforms through the one or more communication devices; …the user segmentation system with the processor…; the user segmentation system with the processor…; …an operating system of the one or more communication devices…; …the one or more communication devices…; …the one or more online platforms through the one or more communication devices… the user segmentation system with the processor; … using one or more machine learning algorithms… training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…; … the user segmentation system with the processor…; …the user segmentation system with the processor…; …at the user segmentation system with the processor… …to the one or more communication devices… one or more communication devices… [Claim 11],
…at a computing device… one or more communication devices…; …the computing device… on one or more online platforms through the one or more communication devices… one or more online platform databases, communication device databases, and third-party databases…; the user segmentation system with the processor…; …an operating system of the one or more communication devices…; …the one or more communication devices…; … the computing device… the one or more online platforms through the one or more communication devices…; … at the computing device… ; … using one or more machine learning algorithms… training of a machine learning model using a supervised machine learning model or an unsupervised machine learning model…; … at the computing device… at the computing device…; …at the user segmentation system with the processor… to the one or more communication devices… one or more communication devices… [Claim 20].
These elements do not amount to significantly more than the abstract idea for the reasons discussed in 2A prong 2 with regard to MPEP 2106.05(a) and MPEP 2106.05(f). By the failure of the elements to integrate the abstract idea into a practical application there, the additional elements likewise fail to amount to an inventive concept that is significantly more than an abstract idea here, in Step 2B.
As such, both individually or in combination, these limitations do not add significantly more to the judicial exception.
The remaining dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the dependent claims do not recite any new additional elements other than those mentioned in the independent claims, which amount to no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)). As such, these claims are not patent eligible.
Prior Art Considerations
Examiner conducted a thorough search of the body of available prior art (see attached documents regards PTO-892 Notice of Reference Cited and PE2E Search History). Notably, Examiner discovered several patent literature documents that taught aspects of the invention, but no single disclosure taught “every element required by the claims under its broadest reasonable interpretation” [MPEP § 2131] to make a 35 USC § 102 rejection. Further, Examiner considered the individual elements of the recited claims taught across the prior art cited below, but did not find it obvious to combine such disclosures [MPEP § 2142] to make a 35 USC § 103 rejection.
In particular, Ferguson et al., U.S. Publication No. 2003/0033194 [hereinafter Ferguson] discloses, a system and method for on-line training of a non-linear model for use in electronic commerce, wherein “Predictive models may be used for analysis, control, and decision making in many areas, including electronic commerce (i.e., e-commerce), e-marketplaces, financial (e.g., stocks and/or bonds) markets and systems, data analysis, data mining, process measurement, optimization (e.g., optimized decision making, real-time optimization), quality control, as well as any other field or domain where predictive or classification models may be useful and where the object being modeled may be expressed abstractly” [Ferguson, ¶ 7]. While Ferguson discloses aspects of the present invention including the personal information and database elements, Ferguson is silent with respect to the particular behavior category and sub-category elements listed in the amended claims.
Further, Zhao, U.S. Publication No. 2021/0081759 [hereinafter Zhao] discloses deep neural network based user segmentation, wherein “the method includes receiving user datasets from a database along with respective user identifiers, retention labels, static user features and interactive user features associated with an online product during a time period” [Zhao, Abstract]. While Zhao discloses aspects of the present invention including user classification data, Zhao does not disclose the particular behavior category and sub-category elements listed in the amended claims.
Further still, Bruckhaus et al., U.S. Patent No. 8,417,715 [hereinafter Bruckhaus] discloses platform independent plug-in methods and systems for data mining and analytics wherein which “comprises extracting and converting data using a data management component into a form usable by a data mining component, performing data mining to develop a model in response to a question or problem posed by a user” [Bruckhaus, Abstract]. While Bruckhaus discloses aspects of the present invention including various types of online platforms for obtaining user data, Bruckhaus is silent with respect to the particular behavior category and sub-category elements recited in the amended claims.
For the above reasons, Examiner determined the currently pending claims novel and non-obvious given the current search. Amendment to the claims and further search in reaction to such amendment may yield the claims anticipated or obvious in future prosecution, determined at that time.
Allowable Subject Matter
Claims 1-9, 11-18 and 20 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Jain et al., U.S. Publication No. 2021/0097384, discloses deep segment personalization.
Chang et al., U.S. Publication No. 2012/0226697, discloses a scalable engine that computes user micro-segments for offer matching.
Cavalin et al., U.S. Publication No. 2017/0177722, discloses segmenting social media users by means of life event detection and entity matching.
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/NICHOLAS D BOLEN/ Examiner, Art Unit 3624
/HAMZEH OBAID/Primary Examiner, Art Unit 3624
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