Techniques for Automatically Generating Biographical Summaries from News Articles

Abstract

The work of manually creating a biographical summary from multiple information sources is both time-intensive and detail-oriented. Automating the task is also non-trivial because of the many natural language processing (NLP) areas that must be used to efficiently extract the relevant facts. Yet, no study has been done to determine how powerful a biographical summarization system must be to achieve the basic goal of filling slots in a biography template. Equally important, the simplest approaches to discovering and extracting biographical information from text have not been implemented. Further, no standard evaluations have been developed for summarization in general, but an evaluation methodology for this research is described and performed.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2007
Accession Number
ADA474074

Entities

People

  • Matthew W. Esparza

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automated Text Summarization
  • Computational Linguistics
  • Computational Science
  • Department Of Defense
  • Information Processing
  • Information Systems
  • International Relations
  • International Trade
  • Jet Propulsion
  • National Security
  • Natural Language Processing
  • Natural Languages
  • Ontologies
  • United States

Readers

  • Computational Linguistics
  • Military History of the United States in the 20th Century.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval