Status of Claims
1. This is a Final office action in response to communication received on 12/02/2025. Claims 1, 3-8, 10-15, and 17-20 are pending and examined herein.
Priority
2. The examiner notes that Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date because fails to comply with 35 U.S.C. 112(a) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or earlier-filed nonprovisional application or provisional application for which benefit is claimed). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed applications (except U.S. Provisional Application No. 61/927,542 filed on January 15, 2014), as per the as-filed specification paragraph [001], fail to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application with respect to notes Figs. 3A-F, 6A-6E, 7A-C, 8A-D, 9A-K and their associated disclosure are supported by the disclosure in the non-provisional, as such, the claims that are supported by the above noted figures and their associated disclosure are not granted priority date of the provisional.
Claim Rejections - 35 USC § 101
3. 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, 3-8, 10-15, and 17-20 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. Next using the 2019 Revised Patent Subject Matter Eligibility Guidances (hereinafter 2019 PEG) the rejection as follows has been applied.
Under step 1, analysis is based on MPEP 2106.03, Claims 1 and 3-7 are a method; claims 8 and 10-14 are a system; and claims 15 and 17-20 are a non-transitory CRM. Thus, each claim 1, 3-8, 10-15, and 17-20, on its face, is directed to one of the statutory categories (i.e., useful process, machine, manufacture, or composition of matter) of 35 U.S.C. §101.
Under Step 2A Prong One, per MPEP 2106.04, prong one asks does the claim recite an abstract idea, law of nature, or natural phenomenon? In Prong One examiners evaluate whether the claim recites a judicial exception, i.e. whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. While the terms "set forth" and "described" are thus both equated with "recite", their different language is intended to indicate that there are two ways in which an exception can be recited in a claim. For instance, the claims in Diehr, 450 U.S. at 178 n. 2, 179 n.5, 191-92, 209 USPQ at 4-5 (1981), clearly stated a mathematical equation in the repetitively calculating step, and the claims in Mayo, 566 U.S. 66, 75-77, 101 USPQ2d 1961, 1967-68 (2012), clearly stated laws of nature in the wherein clause, such that the claims "set forth" an identifiable judicial exception. Alternatively, the claims in Alice Corp., 573 U.S. at 218, 110 USPQ2d at 1982, described the concept of intermediated settlement without ever explicitly using the words "intermediated" or "settlement."
Next, per 2019 PEG, to determine whether a claim recites an abstract idea in Prong One, examiners are now to: (I) Identify the specific limitation(s) in the claim under examination (individually or in combination) that the examiner believes recites an abstract idea; and (II) determine whether the identified limitation(s) falls within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 PEG. If the identified limitation(s) falls within the subject matter groupings of abstract ideas enumerated in Section I, analysis should proceed to Prong Two in order to evaluate whether the claim integrates the abstract idea into a practical application.
(I) An abstract idea as recited per abstract recitation of claims 1, 3-8, 10-15, and 17-20 [i.e. recitation with the exception of additional elements, which are first considered under step 2A prong two when claim(s) is/are reconsidered as a whole and exclusively under step 2B inquiries below, i.e. under step 2A prong one the Examiner considered claim recitation other than the additional elements (which once again are expressly noted below) to be the abstract recitation] (II) is that of sharing user profile comprising interest preference data with one or more merchants as allowed by the user profile’s privacy data which is certain methods of organizing human activity.
The phrase "Certain methods of organizing human activity" applies to fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations {for instance see as-filed spec. para. [0263]}; advertising, marketing or sales activities or behaviors; business relations {(for instance see as-filed spec. paras. [0221]; [0225]}); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). Further, see MPEP 2106.04(a)(2) II. A-C.
Therefore, the identified limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of 2019 PEG, thus analysis now proceeds to Prong Two in order to evaluate whether the claim integrates the abstract idea into a practical application.
Under Step 2A Prong Two, per MPEP 2106.04, prong two asks does the claim recite additional elements that integrate the judicial exception into a practical application? In Prong Two, examiners evaluate whether the claim as a whole integrates the exception into a practical application of that exception. If the additional elements in the claim integrate the recited exception into a practical application of the exception, then the claim is not directed to the judicial exception (Step 2A: NO) and thus is eligible at Pathway B. This concludes the eligibility analysis. If, however, the additional elements do not integrate the exception into a practical application, then the claim is directed to the recited judicial exception (Step 2A: YES), and requires further analysis under Step 2B (where it may still be eligible if it amounts to an ‘‘inventive concept’’).
Next, per 2019 PEG, Prong Two represents a change from prior guidance. The analysis under Prong Two is the same for all claims reciting a judicial exception, whether the exception is an abstract idea, a law of nature, or a natural phenomenon. Examiners evaluate integration into a practical application by: (I) Identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (II) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the considerations laid out by the Supreme Court and the Federal Circuit.
Accordingly, the examiner will evaluate whether the claims recite one or more additional element(s) that integrate the exception into a practical application of that exception by considering them both individually and as a whole.
The claim elements in addition to the abstract idea, i.e. additional elements, as recited in claims at least are per claim 1, a computer-implemented method (as per claim 1); a system, comprising: at least one processor configured to (as per claim 8); a computer program product comprising at least one non- transitory computer-readable medium including program instructions that, when executed by at least one processor, cause the at least one processor to (as per claim 15); electronic payment, a chatbot on a user interface displayed on a user device, database, machine learning comprising a LLM algorithm, receiving/distributing/transmitting, formatting per API of each merchant (per claims 1, 8, 15); interface (per claims 5, 12, 19). Remaining claims either recite the same additional element(s) as already noted above or simply lack recitation of an additional element, in which case note prong one as set forth above.
As would be readily apparent to a person having ordinary skill in the art (hereinafter PHOSITA), the additional elements are generic computer components. The additional elements are simply utilized as generic tools to implement the abstract idea or plan as "apply it" instructions (see MPEP 2106.05(f)). The additional elements are generic as they are described at a high level of generality, see at least as-filed Figs. 1, 3A, 4-5, and their associated disclosure. The processor executing the "apply it" instruction is further connected to one or more device merely sending/receiving/transmitting/obtaining-feedback data over a network, note receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014). Gathered/received data is considered insignificant extra solution activity (see MPEP 2106.05(g)). Further, the processor analyzes received/transmitted/user-feedback data to match and/or update user profile settings. Thus, the process is similar to collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group) - certain result here is a tailored content based on information about the user (Int. Ventures v. Cap One Bank ‘382 patent) that is shared with one or more matched merchant(s) only. The abstract idea is intended to be merely carried out in a technical environment such as collecting data via a network e.g. Internet using a particular interactive interface such as a chatbot and analyzing data via a generic processor to share data with only matched merchants, however fail to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment (see MPEP 2106.05(h)).
Accordingly, viewed as a whole, these additional claim element(s) do not provide any additional element that integrates the abstract idea (prong one), into a practical application (prong two) upon considering the additional elements both individually and as a combination or as a whole as they fail to provide: an additional element that reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field; or an additional element that implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim; or an additional element that effects a transformation or reduction of a particular article to a different state or thing; or an additional element that applies or uses the judicial exception, again, in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception as explained above.
Thus, the abstract idea of sharing user profile comprising interest preference data with one or more merchants as allowed by the user profile’s privacy data (prong one) is not integrated into a practical application upon consideration of the additional element(s) both individually and as a combination (prong two).
Therefore, under step 2A, the claims are directed to the abstract idea, and require further analysis under Step 2B.
Under step 2B, per MPEP 2106.05, as it applies to claims 1, 3-8, 10-15, and 17-20, the Examiner will evaluate whether the foregoing additional elements analyzed under prong two, when considered both individually and as a whole provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). The abstract idea of sharing user profile comprising interest preference data with one or more merchants as allowed by the user profile’s privacy data which is certain methods of organizing human activity - has not been applied in an eligible manner. The claim elements in addition to the abstract idea are simply being utilized as generic tools to execute "apply it" instructions as they are described at a high level of generality. Additionally, the abstract idea is intended to be merely carried out in a technical environment, however fail to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment (Id. or note step 2A prong two).
Regarding, insignificant solution activity such as data gathering or post solution activity such as displaying and/or obtaining feedback via interface, the Examiner relies on court cases and publications that demonstrate that such a way to gather data and display information is indeed well-understood, routine, or conventional in the industry or art, at least note as follows:
(i) receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network) [similarly here user's data is received/transmitted over a network]; and
(iii) Affinity v DirecTV - "The court rejected the argument that the computer components recited in the claims constituted an “inventive concept.” It held that the claims added “only generic computer components such as an ‘interface,’ ‘network,’ and ‘database,’” and that “recitation of generic computer limitations does not make an otherwise ineligible claim patent-eligible.” Id. at 1324-25 (citations omitted). The court noted that nothing in the asserted claims purported to improve the functioning of the computer itself or “effect an improvement in any other technology or technical field.” Mortgage Grader, 811 F.3d at 1325 (quoting Alice, 134 S. Ct. at 2359)." [similarly here user device having an interface is utilized for inputting data and sharing data per merchant API].
Next, in view of compact prosecution only further analysis per the Berkheimer Memo dated April 19, 2018 is being conducted as the following additional elements would be readily apparent as generic to a person having ordinary skill in the art (hereinafter PHOSITA), in other words analysis is similar to Berkheimer claim 1 and not claims 4-7 where there was "a genuine issue of material fact in light of the specification," nevertheless the Examiner finds the additional elements when considered both individually and as a combination to be well-understood, routine or conventional and expressly supports in writing as follows:
The Examiner provides citation to one or more publications as noting the well-understood, routine, conventional nature of machine learning as follows:
i) Chandramouli, Patent: US 8,442,683 note para. [0005]-[0007] and [0029]-[0033]; (ii) Lee, Pub. No.: US 2002/0107926 note para. [0020]; (iii) Kwok, Pub. No.: US 2002/0150295 note para. [0015]; (iv) Teller, Pub. No.: US 2004/0133081 [0236]-[0238]; (v) Agrawal and Srikant Patent No.: US 6546389 note "As recognized herein, the primary task of data mining is the development of models about aggregated data. Accordingly, the present invention understands that it is possible to develop accurate models without access to precise information in individual data records."; (vi) Deshpande et al., Pub. No.: US 2015/0134413 [0046] Using the target and input features, in step F3 of FIG. 1, a plurality of forecasting models are built for a product or a product category, a location, and a time window. A plurality of forecasting models can be built using existing machine learning based methods and/or time-series forecasting methods, and using the standard training-testing-validation methods. In an exemplary embodiment, only the highest quality models with high quality (high accuracy, precision, recall, etc.) are retained.; [0078] The processing system forecasting engine 202 can also include a forecasting model building engine 224 and a forecast calculation engine 226. In the model building stage, target and input features based on a customer or a customer segment's past data are used to train, test, and validate different types of forecasting models using machine learning and/or time series forecasting based approaches. Individual models are retained depending on the performance. The output of plurality of these retained models can then be fused into a single model 228. The fusion can be based on a rule-based approach or by assigning weights to individual model and combining those using ranking or combination techniques." (vii) Wei et al., Pub. No.: US 2015/0235260 [0080] Then, analysis module 532 may determine one or more predefined model(s) 546 based on event data 538 and the one or more targeting criteria. For example, analysis module 532 may use training and testing subsets of this information to generate one or more machine-learning models. The one or more predefined model(s) 546 may allow estimates of the number of future events to be determined for terms 544 in the one or more targeting criteria 542.; (viii) Beatty, Pub. No.: US 2012/0166267 see [0177] note "the prediction of conversion rate is performed by a machine-learning system that is trained using historical purchase data available to the ad system. The training set contains instances of purchase/no purchase decisions and many data points about the (user, context, offer). For example, the training examples might contain the following data points about the offer that was made to a user: price of offer, % discount of offer, popularity of merchant, time of day, gender of user, income of user, interests of user, websites visited by user, categories of websites visited by user, search queries by user, category of business, number of friends that had purchased the offer, "closeness" of friends that had purchased the offer, physical distance between the user's home and the business, physical distance between the user's workplace and the business, the "cluster id" of the user (generated by a clustering algorithm that placed, and users into clusters based on similar attributes of preferences)."
Therefore the claims here fail to contain any additional element(s) or combination of additional elements that can be considered as significantly more and the claims are rejected under 35 U.S.C. 101 for lacking eligible subject matter.
Examiner’s Reason(s) For Withdrawal Of Prior Art
4. The Examiner had relied upon the following references:
Claims 1-2, 4-9, 11-16, and 18-20 were previously rejected under 35 U.S.C. 103(a) as being unpatentable over Maiman et al. (Pub. No.: US2023/0034571) referred to hereinafter as Maiman, in view of Kublickis (Pub. No.: US 2007/0067297).
Claims 3, 10, and 17 were previously rejected under 35 U.S.C. 103(a) as being unpatentable over Maiman in view of Kublickis and Louie et al. (Pub. No.: US2014/0172660) referred to hereinafter as Louie.
The Examiner had previously noted the following:
- Pub. No.: US2023/0205915 see Abstract “systems and techniques that can be implemented by content platforms to optimize (a) demographic- based digital component distribution used to categorize each user into a particular demographic so as to appropriately target that user for purposes of maximizing the efficacy of digital components shown to that user, and (b) demographic reporting used to report to digital component providers the effectiveness of the digital component”; [0002] note “machine learning models are trained based on data collected from multiple sources, e.g., across multiple websites and/or native applications. However, this data may include private or sensitive data that should not be shared or allowed to leak to other parties”
- Pub. No.: US2016/0148182 see Abstract “technologies are disclosed herein for point-of sale customization service. A processor executing a point-of sale customization service can receive a unique identifier associated with a user device detected in a proximity of a computing device. The processor can query preferences stored in a data store using the unique identifier and identify point-of-sale preferences associated with the user device based upon the querying. The processor can transmit the point-of-sale preferences to the computing device to apply to a transaction”; Fig. 4A and its associated disclosure - [0085]-[0092].
While updating the search the Examiner discovered the following:
- Pub. No.: US2024/0267344 see Abstract “chatbot system for filtering conversation content. A chatbot system receives, from a client system, a prompt of a user during an interactive session. The chatbot system filters the prompt of the user based on a set of platform policies and generates a response based on the filtering of the prompt of the user, and communicates the response to the client system”;
[0027] Various examples provide improved user intent detection during conversations with chatbots of an interactive platform. A chatbot, in some examples, is a software application that is designed to simulate human conversation through voice commands or text chats. A chatbot may employ Natural Language Processing (NLP) and Machine Learning (ML)/Artificial Intelligence (AI) methodologies to understand and interpret a user's input and generate a response.
[0028] In some examples, improved user intent detection allows advertisers to bid and target their ads to specific user segments based on a user's intent and interests, which can increase the chances that the user will engage with the ad. Advertisers can have faster ramp up time by providing targeted keywords. In addition, advertisers can benefit from automated creative generation which is based on matching user intent to advertisers' targeted user intent.
[0029] In some examples, a chatbot system provides user intent detection that improves targeting and optimization capabilities over time by analyzing data on user intent and conversions. This enhances the user experience and improves the relevance and performance of ads. Additionally, the interactive platform uses the extracted user intent to enhance the user experience across other portions of the interactive platforming site, making them more personalized and relevant to the user community. In some examples, an interactive platform enhances display advertising by targeting users based on their genuine intent ascertained, in whole or in part, through interaction with a chatbot. By extracting high intent and timely relevant keywords and concepts of conversation with the chatbot, the interactive platform may improve a user intent profile.
[0404] Certain permissions and relationships may be attached to each relationship, and also to each direction of a relationship. For example, a bidirectional relationship (e.g., a friend relationship between individual users) may include authorization for the publication of digital content items between the individual users, but may impose certain restrictions or filters on the publication of such digital content items (e.g., based on content characteristics, location data or time of day data). Similarly, a subscription relationship between an individual user and a commercial user may impose different degrees of restrictions on the publication of digital content from the commercial user to the individual user, and may significantly restrict or block the publication of digital content from the individual user to the commercial user. A particular user, as an example of an entity, may record certain restrictions (e.g., by way of privacy settings) in a record for that entity within the entity table 1008. Such privacy settings may be applied to all types of relationships within the context of the interaction system 100, or may selectively be applied to only certain types of relationships.
[0405] The profile data 1002 stores multiple types of profile data about a particular entity. The profile data 1002 may be selectively used and presented to other users of the interaction system 100 based on privacy settings specified by a particular entity. Where the entity is an individual, the profile data 1002 includes, for example, a username, telephone number, address, settings (e.g., notification and privacy settings), as well as a user-selected avatar representation (or collection of such avatar representations). A particular user may then selectively include one or more of these avatar representations within the content of messages communicated via the interaction system 100, and on map interfaces displayed by interaction clients 104 to other users. The collection of avatar representations may include “status avatars,” which present a graphical representation of a status or activity that the user may select to communicate at a particular time.
- Pub. No.: US20240249318A1 see Abstract “system and method for determining user intent and providing targeted advertising using chatbot interactions is disclosed. The system receives user prompts during chat sessions with a chatbot and generates responses using a large language model. User intent is extracted by analyzing the chat conversations using natural language processing and machine learning techniques. The extracted user intent, comprising weighted keywords and concepts, is used to create a user intent profile. Targeted advertising content is generated based on the user intent profile and provided to the user during subsequent platform interactions. The large language model is continuously retrained using user engagement data to improve intent modeling accuracy. User privacy is maintained by limiting context extraction to chatbot conversations. The system enables personalized and relevant advertising by inferring user intent through conversational interactions”
- Patent No.: US10,796,295 see Abstract “disclosure relates to systems, methods, and devices for processing payment transactions between a user and a merchant using a messaging bot. In particular, a commerce system allows the user to initiate a communications session with a messaging bot associated with the merchant using natural language. One or more embodiments use natural language processing to analyze messages from the user to the messaging bot, and from the messaging bot to the user, to identify a product and a request to purchase the identified product. Based on the identified product and the request to purchase the product, one or more embodiments initiate a payment transaction on behalf of the user based on a natural language conversation and without redirecting the user away from the communications session. Additionally, one or more implementations provide a payment initiation message from the messaging bot to the user indicating that the payment transaction was initiated.”
However, the above noted references were insufficient to establish a prima facie case of obviousness against the claims as amended and filed on 12/02/2025, when the Examiner considered the reference(s) both individually and as a combination.
Therefore the claims overcome the prior art based rejection.
Response to Applicant’s Remarks
5. Rejections under 35 U.S.C. § 101, the Examiner respectfully disagrees with the Applicant’s remarks “directed to improvements to matching algorithms that consider user
preference data submitted directly thereto by the user and that control data representing
a user's current interests. See DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245,
1265 (Fed. Cir. 2014); see also Visual Memory LLC v. NVIDIA Corp., 867 F.3d 1253,
1258 (Fed. Cir. 2017)”; and “The limitations of claim 1 demonstrate that claim 1 is directed to an
unconventional method that improves matching algorithms through the use of a machine
learning system that gives more weight to what a consumer has expressed interest based
on data that is provided by the consumer as opposed to what a merchant and/or an
aggregator is trying to supply to the consumer and the use of data associated with the
consumer to enrich a search signal and data associated with a declared intent of the
consumer with transaction history data.”
The unique facts of the instant application and cited cases are different. The Examiner also notes that the courts have already established, note “even assuming that the algorithms claimed are groundbreaking, innovative or even brilliant, the claims are ineligible because their innovation is an innovation in ineligible subject matter because there are nothing but a series of mathematical algorithms based on selected information and the presentation of the results of those algorithms. Thus, the advance lies entirely in the realm of abstract ideas, with no plausible alleged innovation in the non-abstract application realm. An advance of this nature is ineligible for patenting” (SAP v. Investpic: Page 2, line 22 through Page 3, line 13); and “Even if a process of collecting and analyzing information is limited to particular content, or a particular source, that limitations does not make the collection and analysis other than abstract” (SAP v. Investpic: Page 10, lines 18-24).
Furthermore, well-understood, routine, or conventional applies to additional elements when considered both singularly and in-combination under step 2B, not prong two. Under prong two, the claim when considered as a whole, note “claim elements in addition to the abstract idea, i.e. additional elements, as recited in claims at least are per claim 1, a computer-implemented method (as per claim 1); a system, comprising: at least one processor configured to (as per claim 8); a computer program product comprising at least one non- transitory computer-readable medium including program instructions that, when executed by at least one processor, cause the at least one processor to (as per claim 15); electronic payment, a chatbot on a user interface displayed on a user device, database, machine learning comprising a LLM algorithm, receiving/distributing/transmitting, formatting per API of each merchant (per claims 1, 8, 15); interface (per claims 5, 12, 19). Remaining claims either recite the same additional element(s) as already noted above or simply lack recitation of an additional element, in which case note prong one as set forth above.
As would be readily apparent to a person having ordinary skill in the art (hereinafter PHOSITA), the additional elements are generic computer components. The additional elements are simply utilized as generic tools to implement the abstract idea or plan as "apply it" instructions (see MPEP 2106.05(f)). The additional elements are generic as they are described at a high level of generality, see at least as-filed Figs. 1, 3A, 4-5, and their associated disclosure. The processor executing the "apply it" instruction is further connected to one or more device merely sending/receiving/transmitting/obtaining-feedback data over a network, note receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014). Gathered/received data is considered insignificant extra solution activity (see MPEP 2106.05(g)). Further, the processor analyzes received/transmitted/user-feedback data to match and/or update user profile settings. Thus, the process is similar to collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group) - certain result here is a tailored content based on information about the user (Int. Ventures v. Cap One Bank ‘382 patent) that is shared with one or more matched merchant(s) only. The abstract idea is intended to be merely carried out in a technical environment such as collecting data via a network e.g. Internet using a particular interactive interface such as a chatbot and analyzing data via a generic processor to share data with only matched merchants, however fail to contain meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment (see MPEP 2106.05(h)).
Accordingly, viewed as a whole, these additional claim element(s) do not provide any additional element that integrates the abstract idea (prong one), into a practical application (prong two) upon considering the additional elements both individually and as a combination or as a whole as they fail to provide: an additional element that reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field; or an additional element that implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim; or an additional element that effects a transformation or reduction of a particular article to a different state or thing; or an additional element that applies or uses the judicial exception, again, in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception as explained above.
Thus, the abstract idea of sharing user profile comprising interest preference data with one or more merchants as allowed by the user profile’s privacy data (prong one) is not integrated into a practical application upon consideration of the additional element(s) both individually and as a combination (prong two).
Therefore, under step 2A, the claims are directed to the abstract idea, and require further analysis under Step 2B.”
Lastly, per step 2B, as already established, the additional elements collect data in a technical environment such as network based communication environment e.g. Internet using chatbot as interface. Thus, merely receiving/sending/transmitting data in such environments is considered general linking to a technical environment and data gathered in such environment is insignificant extra solution activity such as pre-solution activity e.g. data gathering (the Examiner provided evidence that such data gathering activity via such additional elements is indeed well-understood, routine, or conventional), which is required for evaluation by a machine learning e.g. LLM algorithm which is described at a high level and executed as “apply it” instructions to process inputted user data to generate an output of a matched one or more merchants with whom the user can be provided based on inputted user transaction, privacy and interest data is indeed not only directed to an abstract idea but lacks significantly more.
Therefore, the Examiner respectfully maintains the rejection.
Conclusion
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and all the references on PTO-892 Notice of Reference Cited should be duly noted by the Applicant as they can be subsequently used during prosecution.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DIPEN M PATEL whose telephone number is (571)272-6519. The examiner can normally be reached Monday-Friday, 08:30-17:00 EST.
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/DIPEN M PATEL/Primary Examiner, Art Unit 3621