Enhancing Detection Through Linguistic Indexing and Topic Expansion

Abstract

Natural language processing techniques may hold a tremendous potential for overcoming the inadequacies of purely quantitative methods of text information retrieval. Under the Tipster contracts in phases I through III, GE group has set out to explore this potential through development and evaluation of new text processing techniques. This work resulted in some significant advances and in a better understanding on how NLP may benefit IR. Tipster research has laid a critical groundwork for future work. In this paper we summarize GE work on document detection in Tipster Phase III. Our summarization research is described in a separate paper appearing in this volume.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1998
Accession Number
ADA631834

Entities

People

  • G. B. Wise
  • Gees C. Stein
  • Tomek Strzalkowski

Organizations

  • General Electric

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Agent Orange
  • Air Traffic Control Systems
  • Automated Text Summarization
  • Computer Science
  • Contracts
  • Control Systems
  • Detection
  • Information Processing
  • Information Retrieval
  • Language
  • Models
  • Natural Language Processing
  • Natural Languages
  • Probabilistic Models
  • Terrorists
  • Test And Evaluation
  • Text Processing

Readers

  • Computational Linguistics
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Information Retrieval
  • AI & ML - Neural Networks