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    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/77997
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/77997


    Title: A semantic frame-based intelligent agent for topic detection
    Authors: Chang, Yung-Chun;Hsieh, Yu-Lun;Chen, Cen-Chieh;Hsu, Wen-Lian
    Contributors: 資訊科學系
    Keywords: Topic detection;Semantic frame;Semantic class;Partial matching
    Date: 2017-01
    Issue Date: 2015-08-27 17:17:22 (UTC+8)
    Abstract: Detecting the topic of documents can help readers construct the background of the topic and facilitate document comprehension. In this paper, we propose a semantic frame-based topic detection (SFTD) that simulates such process in human perception. We take advantage of multiple knowledge sources and extracted discriminative patterns from documents through a highly automated, knowledge-supported frame generation and matching mechanisms. Using a Chinese news corpus containing over 111,000 news articles, we provide a comprehensive performance evaluation which demonstrates that our novel approach can effectively detect the topic of a document by exploiting the syntactic structures, semantic association, and the context within the text. Experimental results show that SFTD is comparable to other well-known topic detection methods.
    Relation: Soft Computing, Volume 21, Issue 2, pp 391–401
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1007/s00500-015-1695-4
    DOI: 10.1007/s00500-015-1695-4
    Appears in Collections:[資訊科學系] 期刊論文

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