Extraction of Relations between Entities from Texts by Learning Methods

Abstract

The aim of this work is to automatically extract structured information from unstructured texts, permitting their fusion in an intelligence application. In Thales, we have a knowledge management system (Ideliance) that permits us to manage entities and relations between them, but at present the user must manually capture this information. To automate such an extraction, we propose the use of a learning algorithm that we have developed after the study of the existing information extraction methods. We present the Sem+ tool that implements the algorithm, and the evaluation of this tool carried out by us and by the Land Headquarter (S.T.A.T. unit).

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2006
Accession Number
ADA474142

Entities

People

  • Benedicte Goujon
  • Julia Frigiere

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Algorithms
  • Artificial Intelligence
  • Automatic
  • Dictionaries
  • Intelligence Domains
  • Ivory Coast
  • Knowledge Management
  • Language
  • Learning
  • Linguistics
  • Machine Learning
  • Natural Languages
  • Strategic Intelligence
  • Supervised Machine Learning
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Database Systems and Applications

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval