Exploiting the role of named entities in query-oriented document summarization

Wenjie Li, Furu Wei, Ouyang You, Qin Lu, Yanxiang He

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


In this paper, we exploit the role of named entities in measuring document/query sentence relevance in query-oriented extractive summarization. Named entity driven associations are defined as the informative, semantic-sensitive text bi-grams consisting of at least one named entity or the semantic class of a named entity. They are extracted automatically according to seven pre-defined templates. Question types are also taken into consideration if they are available when dealing with query questions. To alleviate problems with low coverage, named entity based association and uni-gram models are integrated together to compensate each other in similarity calculation. Automatic ROUGE evaluations indicate that the proposed idea can produce a very good system that among the best-performing system at the DUC 2005.
Original languageEnglish
Title of host publicationPRICAI 2008
Subtitle of host publicationTrends in Artificial Intelligence - 10th Pacific Rim International Conference on Artificial Intelligence, Proceedings
Number of pages10
Publication statusPublished - 1 Dec 2008
Event10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008 - Hanoi, Viet Nam
Duration: 15 Dec 200819 Dec 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5351 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008
Country/TerritoryViet Nam


  • Named entity based association
  • Query-oriented summarization

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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