DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This Office action is in response to Applicant’s communication filed on November 6, 2025. Amendments to claims 1-10 have been entered. Claims 1-10 are pending and have been examined. The statement of reasons for the indication of allowable subject matter over prior art was already discussed in the Office action mailed on August 6, 2025 and hence not repeated here. The claim interpretation, rejections and response to arguments are stated below.
Claim Interpretation
2. Claim 1 recites “A computer-implemented method for processing financial news, comprising:
acquiring news data, invoking a custom-trained topic model to extract entities from the news data, and creating a finite state machine to store entities identified from text of news data and relationships between the entities;
invoking a custom-trained Bidirectional Encoder Representations from Transformers (BERT) model to classify the sentiment of the text to generate sentiment types, and storing the sentiment type in a graph database;
constructing a graph structure based on the entities and the relationships between the entities, optimizing the graph structure, and storing the optimized graph structure in the graph database, wherein the entities are represented as nodes in the graph structure, and the relationships between the entities are represented as edges in the graph structure; and
in response to a query request for the news data from a user being detected, invoking the graph structure associated with the query request and the sentiment type in the graph database for analysis, and generating an analysis result”. It is not clear if these steps of the claim are performed manually and or by a computer processor. Similar ambiguities are also present in the dependent claims 2-7. Appropriate correction/clarification is required. Recitation of “computer-implemented method” in the preamble does not imply that all the steps of the claim are performed by a computer processor. Hence, appropriate correction/clarification is required.
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.
4. Claims 1-10 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
The claim(s) recite(s) computer-implemented method for processing financial news data, which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements as discussed below. This judicial exception is not integrated into a practical application as discussed below. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as discussed below.
Analysis
Step 1: In the instant case, exemplary claim 1 is directed to a method (process).
Step 2A – Prong One: The limitations of “A computer-implemented method for processing financial news data, comprising:
acquiring news data, invoking a custom-trained topic model to extract entities from the news data, and creating a finite state machine to store entities identified from text of news data and relationships between the entities;
invoking a custom-trained Bidirectional Encoder Representations from Transformers (BERT) model to classify the sentiment of the text to generate sentiment types, and storing the sentiment type in a graph database;
constructing a graph structure based on the entities and the relationships between the entities, optimizing the graph structure, and storing the optimized graph structure in the graph database, wherein the entities are represented as nodes in the graph structure, and the relationships between the entities are represented as edges in the graph structure; and
in response to a query request for the news data from a user being detected, invoking the graph structure associated with the query request and the sentiment type in the graph database for analysis, and generating an analysis result” as drafted, when considered collectively as an ordered combination without the italicized portions, is a process that, under the broadest reasonable interpretation, covers the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements.
A computer-implemented method for processing financial news data is a fundamental economic practice such as investment analysis and investment management.
The steps of “acquiring news data, invoking a custom-trained topic model to extract entities from the news data, and creating a finite state machine to store entities identified from text of news data and relationships between the entities;
invoking a custom-trained BERT model to classify the sentiment of the text to generate sentiment types, and storing the sentiment type in a graph database;
constructing a graph structure based on the entities and the relationships between the entities, optimizing the graph structure, and storing the optimized graph structure in the graph database, wherein the entities are represented as nodes in the graph structure, and the relationships between the entities are represented as edges in the graph structure; and
in response to a query request for the news data from a user being detected, invoking the graph structure associated with the query request and the sentiment type in the graph database for analysis, and generating an analysis result” considered collectively is a form of fulfilling agreements between the parties concerned. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
That is, other than, a custom-trained topic model, a finite state machine, a custom-trained Bidirectional Encoder Representations from Transformers (BERT) model, a graph structure, and a graph database, nothing in the claim precludes the steps from being performed as a method of organizing human activity. If the claim limitations, under the broadest reasonable interpretation, covers methods of organizing human activity but for the recitation of generic computer components, then it falls within the “Certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A – Prong Two: The judicial exception is not integrated into a practical application. In particular, the claim only recites the additional elements of a custom-trained topic model, a finite state machine, a custom-trained Bidirectional Encoder Representations from Transformers (BERT) model, a graph structure, and a graph database to perform all the steps. A plain reading of Figures 1-3 and associated descriptions in the Specification reveals that the custom-trained topic model, the custom-trained BERT model, the graph structure may be interpreted broadly to include generic computer components suitably programmed to perform the associated functions. The finite state machine and the graph database are broadly interpreted to include suitably programmed computer storage for storing the corresponding data/ information/models. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, claim 1 is directed to an abstract idea.
Step 2B: The claim does 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, using the additional elements (identified above) to perform the claimed steps amounts to no more than mere instructions to apply the exception using a generic computer component. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, independent claim 1 is not patent eligible. Independent claims 8-10 are also not patent eligible based on similar reasoning and rationale.
Dependent claims 2-7, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations only refine the abstract idea further.
For instance, in claim 2, the steps “wherein the analysis result comprises: detailed information of the graph structure associated with the query request, a risk propagation path of the graph structure associated with the query request, potential correlation of the graph structure associated with the query request, and a future trend of the graph structure associated with the query request” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claim 3, the steps “wherein the step of acquiring news data and invoking a custom-trained topic model to extract entities from the news data particularly comprises:
tagging text in the news data in an Inside-Outside-Beginning (IOB) format using a custom-trained Long Short-Term Memory, Conditional Random Field, Named Entity Recognition (LSTM CRF NER) model to identify entities in the text, and aggregating extracted individual entity tags to identify multi-tag entities” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process. The additional element of a custom-trained LSTM CRF NER model is broadly interpreted to correspond to generic software suitably programmed to perform the associated function. The additional element of the custom-trained LSTM CRF NER model, performs a traditional function recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components.
In claim 4, the steps “wherein after acquiring news data and invoking a custom-trained topic model to extract entities from the news data, the method further comprises: matching the entities with verified finite state machines to create unique identifiers for successfully matched entities” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps further describe the intermediate steps of the underlying process.
In claim 5, the steps “further comprising:
in response to a new entity being identified, acquiring relevant information of the new entity and comparing the relevant information of the new entity with the entity library to generate comparison information; and
in response to determining, according to the comparison information, that the new entity is an entity previously identified with a different name, associating the new entity with the entity previously identified with the different name; or
in response to determining, according to the comparison information, that the new entity has not been identified before, creating a unique identifier to be associated with the new entity” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps further describe the intermediate steps of the underlying process.
In claim 6, the steps “wherein the step of optimizing the graph structure comprises: filtering out noise data, merging similar entities, and eliminating duplicate relationships” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps further describe the intermediate steps of the underlying process.
In claim 7, the steps “wherein the sentiment types comprise positive sentiment, negative sentiment, and neutral sentiment” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the sentiment types used in the intermediate steps of the underlying process.
In all the dependent claims, the judicial exception is not integrated into a practical application because the limitations are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. Also, the claims do not affect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer system itself; the claims do not affect a transformation or reduction of a particular article to a different state or thing; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment. In addition, the dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself. For these reasons, the dependent claims also are not patent eligible.
Response to Arguments
5. In response to Applicant’s arguments about Claim Interpretation on page 5 of the Applicant’s remarks, the amendments have rendered moot most of the ambiguities identified in the last Office action. However, as discussed in the Claim Interpretation section of the current Office action, the limitations that are not clear are maintained by the Examiner. Hence, appropriate correction/clarification is required.
The fact that the claims are Patent-Ineligible when considered under the MPEP 2106 has already been addressed in the rejection and hence not all the details of the rejection are repeated here.
Response to Applicants’ arguments regarding Step 2A – Prong one, Prong two and Step 2B:
The claims recite a computer-implemented method for processing financial news data, which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements as discussed in the rejection. The applicant’s invention may at best be characterized as an improvement in the abstract idea of a computer-implemented method for processing financial news data. An improvement in abstract idea is still abstract (SAP America v. Investpic *2-3 (“We may assume that the techniques claimed are “groundbreaking, innovative, or even brilliant,” but that is not enough for eligibility. Association for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1352 (Fed. Cir. 2014). Nor is it enough for subject-matter eligibility that claimed techniques be novel and nonobvious in light of prior art, passing muster under 35 U.S.C. §§ 102 and 103. See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 89–90 (2012); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (“A claim for a new abstract idea is still an abstract idea). The additional elements (identified in the rejection) are generic computer components used to apply the abstract idea. It does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself.
In response to Applicant’s arguments on pages 7-8 of the remarks, that the claims address a technical problem, not an investment or commercial problem, the Examiner respectfully disagrees. The problems such as “Complexity of Financial News Data: Financial news containing intricate language, specialized terminology, and diverse formats ….. Efficiency and Scalability ….. Lack of Structured Information: Financial news data is often unstructured” may at best be characterized as a problem rooted in the abstract idea of processing financial news data. The Applicants are using the additional elements, as tools in their ordinary capacity, to a problem rooted in an abstract idea. In the instant application, the computer is used in its normal, expected, and routine manner. The claims contain little more than a directive to “use the computer” to implement the abstract idea embraced by the claims. The transformation of an abstract idea into patent-eligible subject matter “requires ‘more than simply stat[ing] the [abstract idea] while adding the words ‘apply it.’’ Alice, 134 S. Ct. at 2357 (quoting Mayo, 132 S. Ct. at 1294). As discussed in the rejection, the claims of the instant case employ a generic system comprising generic components suitably programmed to perform their respective functions. Functions such as “acquiring data; invoking a model for classifying and storing information; constructing graph structures; and invoking the graph structure based on criteria” are conventional functions of a computer system. By relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible (See Alice, 134 S. Ct. at 2359 (use of a computer to create electronic records, track multiple transactions, and issue simultaneous instructions” is not an inventive concept).
The additional elements of the custom-trained topic model, the custom-trained BERT model, the graph structure may be interpreted broadly to include generic computer components suitably programmed to perform the associated functions. The finite state machine and the graph database are broadly interpreted to include suitably programmed computer storage for storing the corresponding data/ information/models. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, the claims are directed to an abstract idea.
The alleged advantages listed on page 8 of the remarks such as “Advanced Natural Language Processing …. Graph Structure Construction and Optimization ….. Integration of Sentiment Analysis with Graph Structure …… Improved Data Processing Efficiency” are due to improvements in the abstract idea of a computer-implemented method for processing financial news data, using the additional elements as tools, in their ordinary capacity, to apply the abstract idea. It does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself.
As discussed in the rejection, the additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, the claims are not patent eligible.
For these reasons and those discussed in the rejection, the rejections under 35 USC § 101 are maintained.
Conclusion
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
(a) Gupta; Akshay et al. (US Pub. 2018/015044 A1) discloses a system comprising a machine-readable storage medium storing at least one program and computer-implemented methods for detecting a language of a text string. Consistent with some embodiments, the method may include applying multiple language identification models to a text string. Each language identification model provides a predicted language of the text string and a confidence score associated with the predicted language. The method may further include weighting each associated confidence score based on historical performance of the corresponding language identification model in predicting languages of other text strings. The method may further include selecting a predicted language of the text string from among the multiple predicted languages provided by the multiple language identification models based on a result of the weighting of the confidence score associated with the particular predicted language.
(b) Duttagupta; Srimoyee et al. (US Pub. 2022/0366490 A1) discloses automatic decisioning associated with unstructured data. Unstructured data, such as that associated with comments of an underwriter regarding a credit decision, can be received. Text mining can be performed to extract features from the unstructured data. The extracted features can subsequently be provided as input to a machine learning model configured to return a prediction of a class associated with the unstructured data. The predicted class, such as approved or rejected, can subsequently be conveyed for display on a display device.
7. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Narayanswamy Subramanian whose telephone number is (571) 272-6751. The examiner can normally be reached Monday-Friday from 9:00 AM to 5:00 PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Abhishek Vyas can be reached at (571) 270-1836. The fax number for Formal or Official faxes and Draft to the Patent Office is (571) 273-8300.
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/Narayanswamy Subramanian/
Primary Examiner
Art Unit 3691
February 23, 2026