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Tractor: A framework for soft information fusion

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Scopus citations

Abstract

This paper presents a soft information fusion framework for creating a propositional graph from natural language messages with an emphasis on producing these graphs for fusion with other messages. The framework utilizes artificial intelligence techniques from natural language understanding, knowledge representation, and information retrieval.

Original languageEnglish
Title of host publication13th Conference on Information Fusion, Fusion 2010
PublisherIEEE Computer Society
ISBN (Print)9780982443811
DOIs
StatePublished - 2010

Publication series

Name13th Conference on Information Fusion, Fusion 2010

Keywords

  • Context
  • Hard/soft data fusion
  • Ontologies
  • Propositional graphs

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