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Incremental summarization using taxonomy

Published: 01 September 2009 Publication History

Abstract

In this paper, a new summarization system is proposed, which summarizes a document by interactively scoring the sentences using already-extracted summary so that the sentence which contains the most amount of relevant information to the summary to be extracted. To calculate the amount of relevant information contained by a sentence, the system makes heavy use of already existing taxonomies. The experiment shows a result pretty close to the current state-of-the-art systems.

References

[1]
Mani, I., "Automatic Summarization", John Benjamins Publishing Company (2001)
[2]
Document understanding conference 2002, available at http://www-nlpir.nist.gov/projects/duc/.
[3]
Radev D. R., Jing, H., Stys, M., Tam, D., "Centroid-based summarization of multiple documents", Information Processing and Management, 40(6):919--938 (2004)
[4]
Mihalcea, R., Tarau, P., "A Language Independent Algorithm for Single and Multiple Document Summarization", Proceedings of IJCNLP (2005)

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  1. Incremental summarization using taxonomy

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    Published In

    cover image ACM Conferences
    K-CAP '09: Proceedings of the fifth international conference on Knowledge capture
    September 2009
    222 pages
    ISBN:9781605586588
    DOI:10.1145/1597735
    • General Chair:
    • Yolanda Gil,
    • Program Chair:
    • Natasha Noy

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 01 September 2009

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    Author Tags

    1. summarization
    2. taxonomy

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    K-CAP '09
    Sponsor:
    K-CAP '09: Fifth International Conference on Knowledge Capture 2009
    September 1 - 4, 2009
    California, Redondo Beach, USA

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    Overall Acceptance Rate 55 of 198 submissions, 28%

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