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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/19/2025 has been entered.
Status of Claims
This is in reply to the claim amendments and remarks of the RCE filed 11/19/2025.
Claims 1 and 11 have been amended.
Claims 1-22 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 .
Response to Amendments
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 1-22, Applicant argues that the claims are patent eligible under 35 USC 101 because the pending claims integrate the abstract idea into a practical application. The Examiner respectfully disagrees. 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. Applicant’s claims recite high level usage of a general-purpose computer and a GPS module for implementing the abstract idea, which merely adds the words apply it with the judicial exception (See MPEP 2106.05). The Examiner asserts that using a training/trained NLP model on a general-purpose computer for implementing the abstract idea merely adds the words apply it with the judicial exception because it to is recited at such a high level of generality and provides nothing more than mere instructions to implement on a computer. Applicant’s arguments are not persuasive.
The Examiner further note that the claims are directed towards Organizing Human Activity. Where merely using a computer and generic machine learning does not make the claims eligible (See MPEP 2106.05). Applicant does not correlate ow McRO, Enfish, or DDR are related to the claims presented. 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 1-22 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 1-10 and 21 are directed toward a process and claims 11-20 and 22 are directed toward a system; which are statutory categories of invention.
Additionally (Step 2A Prong One), the independent claims are directed toward a system for scoring business indices, the system comprising: a mobile cell phone configured to generate geolocation data via hardware and a GPS module; a graphical user interface (GUI); and a non-transitory computer readable medium having stored thereon software instructions, wherein, when performed by a processor, the software instructions are operable to: determine a sentiment score for an article, as directed by via a push of a button on the GUI, wherein the sentiment score is determined according to a one or more sentence sentiments as assigned via an artificial intelligence algorithm, performed in hardware circuitry, that is trained over a range of unstructured content according to a natural language processing model, and wherein a sentence sentiment is generated according to an assessment of modifier polarity; parse each sentence of each article into component parts including verbs, nouns, and modifiers; assign polarity and directionality values to each component part using trained natural language processing (NLP) models; determine a sentence-level sentiment score using a sequence-based sentiment algorithm that computes sentiment directionality from grammatical structure rather than keyword matching; tag each article with one or more signals selected from a taxonomy of predefined risk or growth indicators; correlate the sentiment score with the signal tags to generate a company- specific risk score or growth score; adjust the risk score using predictive modeling trained on historical event- driven datasets to identify statistical indicators of future events, including credit downgrades or bankruptcy risk; analyze the sentiment score according to a correlation against the geolocation data to generate a location-specific sentiment output tied to GPS hardware- derived coordinates; tag the article with an entity, displayed via the GUI, and one or more signals of a plurality of signals, selected via the GUI; display, via the GUI, a daily sentiment score, over time, according the entity; and determine an average sentiment score, as directed by the GUI, according the daily sentiment score and a predetermined time period, displayed via the GUI; and configure a sentiment gauge, according to the entity, to trigger an alert, via email, of a change in the daily sentiment score, wherein: the correlation reflects sentiment trends specific to a geographic location associated with the geolocation data, the daily sentiment score is linked to the geographic location associated with the geolocation data, the average sentiment score reflects sentiment trends specific to the geographic location over the predetermined time period, and the alert is specific to the geographic location associated with the geolocation data, thereby enabling hardware-based geolocation sentiment processing and location-specific business decision-making based on the detected sentiment trends (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 sentiment scores according to sentence sentiment and further determining daily sentiment scores taking into account location for specific location based sentiment decisions to be made based on NLP to determine risk indicators of future events, which is displayed for human use and is organizing how humans interact for commercial purposes.
Dependent claims 2-10 and 12-22 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 “executed by a processor (claim 1)”; “a system, the system comprising: a non-transitory computer readable medium having stored thereon software instructions, wherein, when performed by a processor, the software instructions are operable to (claim 11)”; “a mobile cell phone; via hardware and a GPS module; a graphical user interface (GUI); and as directed by via a push of a button on the GUI, performed in hardware circuitry, using trained natural language processing (NLP) models; displayed via the GUI, selected via the GUI; via the GUI, as directed by the GUI, displayed via the GUI; and via email (claims 1 and 11)”, which are additional elements that do not 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.
The Examiner further notes that the claimed “via an artificial intelligence algorithm that is trained over a range of unstructured content according to a natural language processing model; using trained natural language processing (NLP) models” is recited at such a high level of generality that it merely adds the words apply it with the judicial exception (See MPEP 2106.05). The Examiner specifically points to Applicant’s specification paragraph 0017 which clearly states “The relative magnitude of the sentence sentiment may be assigned according to algorithms, such as artificial intelligence algorithms, that are trained over a range of content”, where the specification provides no details as to what the algorithm is or what it entails. The Examiner further notes that natural language processing is a generic form of machine learning being implemented on a general purpose computer, which again merely adds the words apply it with the judicial exception.
In addition, dependent claims 2-10 and 12-22 further narrow the abstract idea and present no additional elements (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; and System independent claims 1 and 11 recite “executed by a processor (claim 1)”; “a system, the system comprising: a non-transitory computer readable medium having stored thereon software instructions, wherein, when performed by a processor, the software instructions are operable to (claim 11)”; “a mobile cell phone; via hardware and a GPS module; a graphical user interface (GUI); and as directed by via a push of a button on the GUI, performed in hardware circuitry, using trained natural language processing (NLP) models; displayed via the GUI, selected via the GUI; via the GUI, as directed by the GUI, displayed via the GUI; and via email (claims 1 and 11)”; 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 Paragraph 0016. 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. 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 2-10 and 12-22 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. 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 1-22 are allowable over the prior art, but remain rejected under §101 for the reasons set forth above. Independent claims 1 and 11 disclose a system and method for analyzing sentiment scores according to sentence sentiment and further determining daily sentiment scores taking into account location for specific location based sentiment decisions to be made based on NLP to determine risk indicators of future events.
Regarding a possible 103 rejection: The closest prior art of record is:
Goodbole et al. (US 2008/0270116 A1) – which discloses large scale sentiment analysis using NLP.
Sisk (US 2013/0138577 A1) – which discloses predicting market behavior based on news and sentiment analysis.
Moudy et al. (US 2016/0300135 A1) – which discloses a relative sentiment analyzer.
The prior art of record neither teaches nor suggests all particulars of the limitations as recited in claims 1 and 11, such as analyzing sentiment scores according to sentence sentiment and further determining daily sentiment scores taking into account location for specific location based sentiment decisions to be made based on NLP to determine risk indicators of future events. 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 system for scoring business indices, the system comprising: a mobile cell phone configured to generate geolocation data via hardware and a GPS module; a graphical user interface (GUI); and a non-transitory computer readable medium having stored thereon software instructions, wherein, when performed by a processor, the software instructions are operable to: determine a sentiment score for an article, as directed by via a push of a button on the GUI, wherein the sentiment score is determined according to a one or more sentence sentiments as assigned via an artificial intelligence algorithm, performed in hardware circuitry, that is trained over a range of unstructured content according to a natural language processing model, and wherein a sentence sentiment is generated according to an assessment of modifier polarity; parse each sentence of each article into component parts including verbs, nouns, and modifiers; assign polarity and directionality values to each component part using trained natural language processing (NLP) models; determine a sentence-level sentiment score using a sequence-based sentiment algorithm that computes sentiment directionality from grammatical structure rather than keyword matching; tag each article with one or more signals selected from a taxonomy of predefined risk or growth indicators; correlate the sentiment score with the signal tags to generate a company- specific risk score or growth score; adjust the risk score using predictive modeling trained on historical event- driven datasets to identify statistical indicators of future events, including credit downgrades or bankruptcy risk; analyze the sentiment score according to a correlation against the geolocation data to generate a location-specific sentiment output tied to GPS hardware- derived coordinates; tag the article with an entity, displayed via the GUI, and one or more signals of a plurality of signals, selected via the GUI; display, via the GUI, a daily sentiment score, over time, according the entity; and determine an average sentiment score, as directed by the GUI, according the daily sentiment score and a predetermined time period, displayed via the GUI; and configure a sentiment gauge, according to the entity, to trigger an alert, via email, of a change in the daily sentiment score, wherein: the correlation reflects sentiment trends specific to a geographic location associated with the geolocation data, the daily sentiment score is linked to the geographic location associated with the geolocation data, the average sentiment score reflects sentiment trends specific to the geographic location over the predetermined time period, and the alert is specific to the geographic location associated with the geolocation data, thereby enabling hardware-based geolocation sentiment processing and location-specific business decision-making based on the detected sentiment trends (as required by independent claims 1 and 11)”, thus rendering claims 1, 11, 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.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MATTHEW D HENRY/Primary Examiner, Art Unit 3625