DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 8/7/2026 has been entered.
Status of Claims
This is in reply to the claim amendments and remarks of the RCE filed 8/7/2026.
Claims 1, 14, and 20 have been amended.
Claims 1-2, 4-5, 7-10, 13-17, and 20 are currently pending and have been examined.
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 .
Priority
This application claims priority of Provisional Application 63/533994 filed on 8/22/2023. Applicant's claim for the benefit of this prior-filed application is acknowledged.
Response to Amendments
All claims are now directed towards a statutory category of invention.
Applicant’s amendments have been fully considered, but do not overcome the previously pending 35 USC 101 rejections.
Response to Arguments
Applicant's arguments have been fully considered but they are not persuasive.
With regard to the limitations of claims 1-2, 4-5, 7-10, 13-17, and 20, Applicant argues that the claims are patent eligible under 35 USC 101 because the pending claims do not recite generic machine learning. The Examiner respectfully disagrees. Applicant states the vector embedding generation using an encoding process improves the computer process, but does not define what the vector embedding entails or what the encoding process even is. The steps/functions are recited at such a high level of generality that they would merely add the words apply it with the judicial exception (See MPEP 2106.05), where the vector embedding appears to be merely inputting data into a vector. The Examiner also notes that generic use of an API also merely adds the words apply it with the judicial exception. Applicant’s arguments are not persuasive.
The Examiner notes that retrieving data using an API from a plurality of network sources and a database is recited at such a high level of generality that it merely amounts to instructions to implement the data collection on a general purpose computer, which does not integrate the abstract idea into a practical application (See MPEP 2106.05). Applicant’s arguments are not persuasive.
The Examiner has clearly pointed out the limitations directed towards the abstract idea, what the additional elements are and why they do not integrate the abstract idea into a practical application, and why the additional elements and remaining limitations do not amount to significantly more than the abstract idea. The examiner has considered all claim limitations in a full analysis including the additional limitations individually and in an ordered combination. Applicant does not point out how the Examiner’s rejection is in error. Applicant’s arguments are not persuasive.
Applicant argues the claims are related to Example 2. The Examiner respectfully disagree. The Applicant’s claims do not recite any details regarding keeping visitors on a webpage and in fact do not recite a webpage of any kind. The Applicant’s claims do not recite any specific arrangement or specifics in display technology beyond generic use of general purpose computer components. Applicant does not properly identify the additional elements. Applicant’s arguments are not persuasive.
Applicant argues the claims are related to Example 21. The Examiner respectfully disagree. The Applicant’s claims do not recite any details regarding how data is transmitted or involve stock trading in any manner. The Applicant’s claims do not recite any specific arrangement or specifics in display or transmission technology beyond generic use of general purpose computer components. The Examiner also notes that transmitting an alert when a threshold was met was not the reason the claims were determined to be eligible. Applicant does not properly identify the additional elements. Applicant’s arguments are not persuasive.
Applicant argues there is a specific technological arrangement that makes the claims eligible. The Examiner respectfully disagrees. The Applicant’s claims recite vector embedding (e.g. inputting data into a vector), use of an API (e.g. general purpose computer components), using an embedding model (the embedding model is not specifically defined and merely amounts to use of a model for inputting data), and using a large language model (recited at such a high level of generality it merely adds the words apply it with the judicial exception). The Examiner asserts that inputting data into a vector and using an LLM is not a technical solution, but rather merely use of technology for implementing the abstract idea. The Applicant’s claimed limitations do not appear to bring about any improvement in the operation or functioning of a computer per se, or to improve computer-related technology by allowing computer performance of a function not previously performable by a computer (see page 2 of the McRo-Bascom memo). The solution appears to be more of a business-driven solution rather than a technical one. Applicant’s arguments are not persuasive.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 4-5, 7-10, 13-17, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter;
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself.
In the instant case (Step 1), claims 1-2, 4-5, 7-10, and 13 are directed toward a process, 14-17 are directed toward a system, and claim 20 is directed towards a product, which are statutory categories of invention
Additionally (Step 2A Prong One), the independent claims are directed toward a method for generating a personalized analysis for a user of network based content obtained from a plurality of network sources using a user profile of the user in conjunction with a large language model (LLM), the network sources available over a communications network, the method comprising the steps of: assembling the user profile to contain user profile data including financial instrument information for a set of financial instruments selected from the group consisting of: stocks; bonds; mutual funds; exchange-traded funds; and real estate investment trusts, and user interest data associated with the user, the financial information comprising a first history of instrument trading performed by the user, and the user interest data comprising a second history of user selected content corresponding to the financial instruments obtained from the plurality of network sources comprising reading materials, stock tickers, earnings report, and/or market sectors; storing the user profile data for the first history in a storage for use as a set of content search parameters and storing user interest data for the second history in the storage for use as a set of content filters; generating a vector embedding from the content search parameters by encoding information selected from the group consisting of: text data; documents; image data; and audio data from the first history into a numerical vector representation of the content search parameters; retrieving a plurality of news articles from a set of network sources using an application programming interface and querying additional financial information from an external database, the set of network sources selected from the plurality of network sources, and the plurality of news articles and the additional financial information forming the network based content; processing the vector embedding using an embedding model to determine matching news articles by comparing the content search parameters to the network based content using the embeddings model; processing the matching news articles and one or more content filters from the set of content filters using an LLM in order to derive a chain of thought based output relevant to the matching news articles and the one or more content filters; requesting the LLM to determine one or more insights using the chain of thought based output in order to generate the personalized analysis, comprising parsing the matching news articles using the LLM to further filter the matching news articles using the one or more content filters; generating an insight notification to include the personalized analysis including the one or more insights; and sending the insight notification over the communications network to the user for subsequent processing (claims 1, 14, and 20) (Organizing Human Activity), which are considered to be abstract ideas (See MPEP 2106.05). The steps/functions disclosed above and in the independent claims are directed toward the abstract idea of Organizing Human Activity because the claimed limitations are analyzing financial instrument information compared to interest data to see what news articles match input parameters and determining insights of personal users to make determinations using models and vectors, which is a commercial interaction.
Dependent claims 2, 4-5, 7-10, 13, and 15-17 further narrow the abstract idea identified in the independent claims, where any additional elements introduced are discussed below.
Step 2A Prong Two: In this application, even if not directed toward the abstract idea, the independent claims additionally recite “storing the user profile data in a storage; storing user interest data in the storage (claims 1, 14, and 20)”, which are additional elements that do not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because receiving/storing data merely add insignificant extra-solution activity and merely adds the words to apply it with the judicial exception. Also, the independent claims additionally recite “a plurality of network sources; the network sources available over a communications network; in a storage; using an application programming interface; from an external database (claim 1);” “computer system; the system comprising: one or more computer processors to; a plurality of network sources; the network sources available over a communications network; in a storage; using an application programming interface; from an external database (claim 14);” “non-transitory computer readable medium having stored thereon computer readable instructions which when executed by a computer processor configure the computer processor to perform a method; a plurality of network sources; the network sources available over a communications network; in a storage; using an application programming interface; from an external database (claim 20)”, which are additional elements that do not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because the claimed structure merely adds the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See MPEP 2106.05) and are recited at such a high level of generality. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. Even when viewed in combination, the additional elements in the claims do no more than use the computer components as a tool. There is no change to the computer or other technology that is recited in the claim, and thus the claims do not improve computer functionality or other technology.
In addition, dependent claims 2, 4-5, 7-10, 13, and 15-17 further narrow the abstract idea and recite no additional elements that integrate the abstract idea into a practical application. The claims merely add the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See MPEP 2106.05).
Step 2B: When analyzing the additional element(s) and/or combination of elements in the claim(s) other than the abstract idea per se the claim limitations amount(s) to no more than: a general link of the use of an abstract idea to a particular technological environment and merely amounts to the application or instructions to apply the abstract idea on a computer (See MPEP 2106.05). Further, method; System; and Product Independent claims 1, 14, and 20 recite “a plurality of network sources; the network sources available over a communications network; in a storage; using an application programming interface; from an external database (claim 1);” “computer system; the system comprising: one or more computer processors to; a plurality of network sources; the network sources available over a communications network; in a storage; using an application programming interface; from an external database (claim 14);” “non-transitory computer readable medium having stored thereon computer readable instructions which when executed by a computer processor configure the computer processor to perform a method; a plurality of network sources; the network sources available over a communications network; in a storage; using an application programming interface; from an external database (claim 20)”; however, these elements merely facilitate the claimed functions at a high level of generality and they perform conventional functions and are considered to be general purpose computer components which is supported by Applicant’s specification in Paragraphs 0040 and Figures 1-2. The Applicant’s claimed additional elements are mere instructions to implement the abstract idea on a general purpose computer and generally link of the use of an abstract idea to a particular technological environment. Also, the independent claims additionally recite “storing the user profile data in a storage; storing user interest data in the storage (claims 1, 14, and 20)”, which are additional elements that do not account for significantly more than the abstract idea because storing data (See MPEP 2106.05) have been identified as well-known, routine, and conventional steps/functions to one of ordinary skill in the art. When viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
In addition, claims 2, 4-5, 7-10, 13, and 15-17 further narrow the abstract idea identified in the independent claims and present no additional elements that provide significantly more. The Examiner notes that the dependent claims merely further define the data being analyzed and how the data is being analyzed (See MPEP 2106.05). The additional limitations of the independent and dependent claim(s) when considered individually and as an ordered combination do not amount to significantly more than the abstract idea. The examiner has considered the dependent claims in a full analysis including the additional limitations individually and in combination as analyzed in the independent claim(s). Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Allowable over 35 USC 103
Claims 1-2, 4-5, 7-10, 13-17, and 20 are allowable over the prior art, but remain rejected under §101 for the reasons set forth above. Independent claims 1, 14, and 20 disclose generating a personalized analysis for a user by assembling a profile of financial information containing histories, generating vector embeddings from the search parameters by encoding specific pieces of information and processing the embeddings to determine matching news articles and using a LLM to determine insights from the chain of thought by parsing the news articles and outputting the results.
Regarding a possible 103 rejection: The closest prior art of record is:
Sumant (US 2023/0245234 A1) – which discloses integrate cash network decision optimization for budgeting and forecasting (See previous OA citations).
Stading (US 2008/0243785 A1) – which discloses determining search results based on specific users and specific inputs (See previous OA citations).
Zhou (US 2025/0348911 A1) – which discloses analyzing stored data using different AI and LLM’s to rank outputs that should be given to users (See previous OA citations).
The prior art of record neither teaches nor suggests all particulars of the limitations as recited in claims 1, 14, and 20, such as generating a personalized analysis for a user by assembling a profile of financial information containing histories, generating vector embeddings from the search parameters by encoding specific pieces of information and processing the embeddings to determine matching news articles and using a LLM to determine insights from the chain of thought by parsing the news articles and outputting the results. While individual features may be known per se, there is no teaching or suggestion absent applicants’ own disclosure to combine these features other than with impermissible hindsight and the combination/arrangement of features are not found in analogous art. Specifically the claimed “a method for generating a personalized analysis for a user of network based content obtained from a plurality of network sources using a user profile of the user in conjunction with a large language model (LLM), the network sources available over a communications network, the method comprising the steps of: assembling the user profile to contain user profile data including financial instrument information for a set of financial instruments selected from the group consisting of: stocks; bonds; mutual funds; exchange-traded funds; and real estate investment trusts, and user interest data associated with the user, the financial information comprising a first history of instrument trading performed by the user, and the user interest data comprising a second history of user selected content corresponding to the financial instruments obtained from the plurality of network sources comprising reading materials, stock tickers, earnings report, and/or market sectors; storing the user profile data for the first history in a storage for use as a set of content search parameters and storing user interest data for the second history in the storage for use as a set of content filters; generating a vector embedding from the content search parameters by encoding information selected from the group consisting of: text data; documents; image data; and audio data from the first history into a numerical vector representation of the content search parameters; retrieving a plurality of news articles from a set of network sources using an application programming interface and querying additional financial information from an external database, the set of network sources selected from the plurality of network sources, and the plurality of news articles and the additional financial information forming the network based content; processing the vector embedding using an embedding model to determine matching news articles by comparing the content search parameters to the network based content using the embeddings model; processing the matching news articles and one or more content filters from the set of content filters using an LLM in order to derive a chain of thought based output relevant to the matching news articles and the one or more content filters; requesting the LLM to determine one or more insights using the chain of thought based output in order to generate the personalized analysis, comprising parsing the matching news articles using the LLM to further filter the matching news articles using the one or more content filters; generating an insight notification to include the personalized analysis including the one or more insights; and sending the insight notification over the communications network to the user for subsequent processing (as required by independent claims 1, 14, and 20)”, thus rendering claims 1, 14, 20 and their dependent claims as allowable over the prior art.
Conclusion
The prior art made of record, but not relied upon is considered pertinent to Applicant's disclosure is listed on the attached PTO-892 and should be taken into account / considered by the Applicant upon reviewing this office action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW D HENRY whose telephone number is (571)270-0504. The examiner can normally be reached on Monday-Thursday 9AM-5PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, BRIAN EPSTEIN can be reached on (571)-270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MATTHEW D HENRY/Primary Examiner, Art Unit 3625
