Lawrence Livermore National Security, LLC

William G Hanley

Tracy D Lemmond

Ryan Prenger

John J Nitao

David A Knapp

Kofi Boakye

Ron E Glaser

Barry Y Chen

Joseph Wendell Guensche

Lawrence J Hiller

Nathan C Perry

Marshall J Mugge

Paul Brandon Kidwell

An information extraction system and methods of operating the system are provided. In particular, an information extraction system for performing meta-extraction of named entities of people, organizations, and locations as well as relationships and events from text documents are described herein.

Information extraction system

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Discriminant forest classification method and system

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Livermore, CA, United States of America

William G Hanley