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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/39686


    Title: Ontology-based text summarization for business news articles
    Authors: 劉昭麟
    Wu, Chia-wei;Liu, Chao-lin
    Contributors: 國立政治大學資訊科學系
    Keywords: Ontology-based text summarization;business news articles
    Date: 2003-03
    Issue Date: 2010-05-27 16:48:33 (UTC+8)
    Abstract: In this paper, we compare two methods for article summarization. The first method is mainly based on term-frequency, while the second method is based on ontology. We build an ontology database for analyzing the main topics of the article. After identifying the main topics and determining their relative significance, we rank the paragraphs based on the relevance between main topics and each individual paragraph. Depending on the ranks, we choose desired proportion of para- graphs as summary. Experimental results indicate that both methods offer similar accuracy in their selections of the paragraphs.
    Relation: Proceedings of the ISCA Eighteenth International Conference on Computers and Their Applications
    Data Type: conference
    Appears in Collections:[Department of Computer Science ] Proceedings

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