Event-based summarization using critical temporal event term chain

Maofu Liu, Wenjie Li, Xiaolong Zhang, Ji Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


In this paper, we investigate whether temporal relations among event terms can help improve event-based summarization and text cohesion of final summaries. By connecting event terms with happens-before relations, we build a temporal event term graph for source documents. The event terms in the critical temporal event term chain identified from the maximal weakly connected component are used to evaluate the sentences in source documents. The most significant sentences are included in final summaries. Experiments conducted on the DUC 2001 corpus show that event-based summarization using the critical temporal event term chain is able to organize final summaries in a more coherent way and make improvement over the well-known tf idf-based and PageRank-based summarization approaches.
Original languageEnglish
Title of host publicationComputer Processing of Oriental Languages
Subtitle of host publicationLanguage Technology for the Knowledge-based Economy - 22nd International Conference, ICCPOL 2009, Proceedings
Number of pages8
Publication statusPublished - 9 Nov 2009
Event22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009 - , Hong Kong
Duration: 26 Mar 200927 Mar 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5459 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Computer Processing of Oriental Languages, ICCPOL 2009
Country/TerritoryHong Kong


  • Depth-First Search Algorithm
  • Event Term Graph
  • Event-Based Summarization
  • Temporal Event Term Chain

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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