A new approach to blog post summarization using fast features

  • Shuang Sun*
  • , Zhao Lv
  • , Liang He
  • , Junzhong Gu
  • *Corresponding author for this work

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

1 Scopus citations

Abstract

Blog post summarization using fast features facilitates users' quick browsing through blog search results. Much existing research on blogs ignores blog tags and text structure. In this paper, we re-formalize the blog post summarization problem as a sentence extraction and sentence ranking problem. Three fast features, important sentences, blog tags and blog comments, are proposed to calculate salience scores of representative words. Then we propose an average-summation-based sentence selection method called ASS to select sentences based on the salience scores of content words in sentences. As been used to evaluate on human-labeled sentences, ASS showed anticipated results.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Pages8-13
Number of pages6
DOIs
StatePublished - 2008
Event5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 - Jinan, Shandong, China
Duration: 18 Oct 200820 Oct 2008

Publication series

NameProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Volume2

Conference

Conference5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
Country/TerritoryChina
CityJinan, Shandong
Period18/10/0820/10/08

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