A semantic frame-based intelligent agent for topic detection

Yung Chun Chang, Yu Lun Hsieh, Cen Chieh Chen, Wen Lian Hsu

研究成果: 雜誌貢獻文章同行評審

10 引文 斯高帕斯(Scopus)

摘要

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.
原文英語
頁(從 - 到)391-401
頁數11
期刊Soft Computing
21
發行號2
DOIs
出版狀態已發佈 - 一月 1 2017
對外發佈

ASJC Scopus subject areas

  • 理論電腦科學
  • 軟體
  • 幾何和拓撲

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