Deriving event relevance from the ontology constructed with formal concept analysis

Wei Xu, Wenjie Li, Mingli Wu, Wei Li, Chunfa Yuan

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

8 Citations (Scopus)

Abstract

In this paper, we present a novel approach to derive event relevance from event ontology constructed with Formal Concept Analysis (FCA), a mathematical approach to data analysis and knowledge representation. The ontology is built from a set of relevant documents and according to the named entities associated to the events. Various relevance measures are explored, from binary to scaled, and from symmetrical to asymmetrical associations. We then apply the derived event relevance to the task of multi-document summarization. The experiments on DUC 2004 data set show that the relevant-event-based approaches outperform the independent-event-based approach.
Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 7th International Conference, CICLing 2006, Proceedings
Pages480-489
Number of pages10
DOIs
Publication statusPublished - 7 Jul 2006
Event7th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2006 - Mexico City, Mexico
Duration: 19 Feb 200625 Feb 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3878 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2006
CountryMexico
CityMexico City
Period19/02/0625/02/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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