Patent №
US 6,502,081
Granted
2002-12-31
Filed 2000
Owner
LEXIS NEXIS
+1 more
Lab
—
AI components
6
ml · nlp · vision · kr · planning · hardware
Assignment
Recorded
Dataset
AIPD
2023_r1 edition
Application
09633266
An economic, scalable machine learning system and process perform document (concept) classification with high accuracy using large topic schemes, including large hierarchical topic schemes. One or more highly relevant classification topics is suggested for a-given document (concept) to be classified. The invention includes training and concept classification processes. The invention also provides methods that may be used as part of the training and/or concept classification processes, including: a method of scoring the relevance of features in training concepts, a method of ranking concepts based on relevance score, and a method of voting on topics associated with an input concept. In a preferred embodiment, the invention is applied to the legal (case law) domain, classifying legal concepts (rules of law) according to a proprietary legal topic classification scheme (a hierarchical scheme of areas of law).
AI classification
Ownership
LEXIS NEXIS
assignment · 133650128
LEXISNEXIS, A DIVISION OF REED ELSEVIER INC.
correct · 251310067
Assignors
WILTSHIRE, JR., JAMES S., MORELOCK, JOHN T., HUMPHREY, TIMOTHY L., LU, X. ALLAN, PECK, JAMES M., AHMED, SALAHUDDIN
On an employer assignment, the assignors are typically the inventors.