Automatic text summarizing based on sentence extraction: A statistical approach

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

Automatic text summarizing based on sentence extraction: A statistical approach

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

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	19-23
Number of pages	5
Journal	International Journal of Applied Electromagnetics and Mechanics
Volume	13
Issue number	1-4 SPEC.
Publication status	Published - 2001 Dec 1
Externally published	Yes

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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