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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 12236497 B1

PDFFull Text
Date of Patent:
Feb. 25, 2025

Filed:

Apr. 21, 2017

Systems and methods for predicting policy adoption

Applicant:

Fiscalnote, Inc., Washington, DC (US);

Inventors:

Brian Grom, Lake Worth, FL (US);

Vladimir Eidelman, Chevy Chase, MD (US);

Daniel Argyle, Alexandria, VA (US);

Jervis Pinto, Md, IN;

Assignee:

FiscalNote, Inc., Washington, DC (US);

Attorney:

Finnegan, Henderson, Farabow, Garrett & Dunner

Primary Examiner:

Hafiz A Kassim

Assistant Examiner:

Scott M Ross

Int. Cl.
CPC ...
G06Q 10/00 (2023.01); G06F 3/0482 (2013.01); G06F 3/04847 (2022.01); G06F 16/28 (2019.01); G06F 16/3331 (2025.01); G06F 40/205 (2020.01); G06F 40/263 (2020.01); G06F 40/30 (2020.01); G06N 5/022 (2023.01); G06N 5/04 (2023.01); G06Q 10/0637 (2023.01); G06Q 50/18 (2012.01); G06Q 50/26 (2012.01); G06F 16/95 (2019.01); G06N 20/00 (2019.01); G06T 11/20 (2006.01);
U.S. Cl.
CPC ...
G06Q 50/26 (2013.01); G06F 3/0482 (2013.01); G06F 3/04847 (2013.01); G06F 16/288 (2019.01); G06F 16/3331 (2019.01); G06F 40/205 (2020.01); G06F 40/263 (2020.01); G06F 40/30 (2020.01); G06N 5/022 (2013.01); G06N 5/04 (2013.01); G06Q 10/06375 (2013.01); G06Q 50/18 (2013.01); G06F 16/95 (2019.01); G06N 20/00 (2019.01); G06Q 2230/00 (2013.01); G06T 11/206 (2013.01); G06T 2200/24 (2013.01);
Abstract

A text analytics system may predict whether a policy will be adopted. The system may include at least one processor configured to access information scraped from the Internet to identify text data associated with comments expressed by a plurality of individuals about a proposed policy. The at least one processor may be further configured to analyze the text data in order to determine a sentiment of each comment; apply an influence filter to each comment to determine an influence metric associated with each comment; weight each comment using the influence metric; determine based on an aggregate of the weighted comments, an indicator associated with adoption of the policy; and transmit the indicator to a system user.

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