SYSTEMS AND METHODS FOR IDENTIFYING A RISK OF IMPLIEDLY OVERRULED CONTENT BASED ON CITATIONALLY RELATED CONTENT

Patent №

US 11,615,492

Granted

2023-03-28

Filed 2019

Owner

THOMSON REUTERS CANADA LIMITED

+4 more

Lab

AI components

7

ml · nlp · vision · speech · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16411809

The present disclosure relates to systems and methods for analyzing citationally related content and identifying, based on the analysis, a risk of impliedly overruled content. Embodiments provide for receiving case law data from a document source, for extracting a case triple that includes a first case overruling or abrogating a second case, and a third case citationally related to the second case. Features may be generated from case triple, such as natural processing language features comparing the language in the various cases of the triple, and feeding the generated features to a main classifier. In embodiments, the main classifier classifies the case triple into a class indicating the risk probability that the second case is impliedly overruled by the first case.

AI classification

Natural language1.00
Planning1.00
Machine learning1.00
Knowledge representation1.00
Speech1.00
Vision1.00
AI hardware0.55
Evolutionary computation0.00

Ownership

THOMSON REUTERS CANADA LIMITED

assignment · 523280828

THOMSON REUTERS HOLDINGS INC.

assignment · 523290228

WEST PUBLISHING CORPORATION

assignment · 523290384

THOMSON REUTERS GLOBAL RESOURCES UNLIMITED COMPANY

assignment · 523290448

THOMSON REUTERS ENTERPRISE CENTRE GMBH

assignment · 523400914

Assignors

BROOKE, JULIAN, MADAN, KANIKA, ALONSO, HECTOR MARTINEZ, FAZLY, AFSANEH, CUSTIS, TONYA, MOULINIER, ISABELLE, MCELVAIN, GAYLE, ERICKSON, DIANE

On an employer assignment, the assignors are typically the inventors.

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