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Exploiting the Role of Named Entities in Query-Oriented Document Summarization

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Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 5351))

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Abstract

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.

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Author information

Authors and Affiliations

  1. Department of Computing, The Hong Kong Polytechnic University, Hong Kong

    Wenjie Li, Furu Wei, Ouyang You & Qin Lu

  2. Department of Computer Science and Technology, Wuhan University, China

    Furu Wei & Yanxiang He

Authors
  1. Wenjie Li

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  2. Furu Wei

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  3. Ouyang You

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  4. Qin Lu

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  5. Yanxiang He

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Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Asahidai 1-1, 923-12292, Nomi, Japan

    Tu-Bao Ho

  2. Department of Computer Science & Technology, Nanjing University, 22 Hankou Road, 210093, China

    Zhi-Hua Zhou

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© 2008 Springer-Verlag Berlin Heidelberg

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Li, W., Wei, F., You, O., Lu, Q., He, Y. (2008). Exploiting the Role of Named Entities in Query-Oriented Document Summarization. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_68

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