Sentence descending algorithm for automatic text summarization

Tiedan Zhu*, Qiongxin Liu

*Corresponding author for this work

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

Abstract

This paper proposes a novel method for automatic text summarization. The topic space model is built through the Chinese Restaurant Process. The documents are mapped to the topic space from vector space. Sentence descending algorithm is introduced to create the summary. An experiment is illustrated on DUC2006 data and the results prove the proposed method effective and well performed.

Original languageEnglish
Title of host publicationProceedings - 2011 International Conference on Computational and Information Sciences, ICCIS 2011
Pages301-304
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 International Conference on Computational and Information Sciences, ICCIS 2011 - Chengdu, Sichuan, China
Duration: 21 Oct 201123 Oct 2011

Publication series

NameProceedings - 2011 International Conference on Computational and Information Sciences, ICCIS 2011

Conference

Conference2011 International Conference on Computational and Information Sciences, ICCIS 2011
Country/TerritoryChina
CityChengdu, Sichuan
Period21/10/1123/10/11

Keywords

  • Automatic Text Summarization
  • Chinese Restaurant Process
  • Sentence descending algorithm
  • Topic Space Model

Fingerprint

Dive into the research topics of 'Sentence descending algorithm for automatic text summarization'. Together they form a unique fingerprint.

Cite this