Automatic text summarizing based on sentence extraction: A statistical approach

Bogdan Cranganu-Cretu, Zhenmao Chen, Tetsuya Uchimoto, Kenzo Miya

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The present work describes a system for automatic summarizing of texts. Rather than focusing on abstracts C a hard NLP task of not asserted effectiveness the system produces extracts through selection of most important sentences in the original text. Statistical concepts are involved in order to evaluate the degree of significance of words, groups of words and sentences. Currently both Japanese and English texts can be treated. Procedures for computing importance, information content of sentences and measures of correlation between sentences are implemented. Comments are given on the feasibility of the approach and future developments.

Original languageEnglish
Pages (from-to)19-23
Number of pages5
JournalInternational Journal of Applied Electromagnetics and Mechanics
Volume13
Issue number1-4 SPEC.
Publication statusPublished - 2001 Dec 1
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Electrical and Electronic Engineering

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