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Automatic thesaurus generation for Chinese documents

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  • Yuen‐Hsien Tseng

Abstract

This article reports an approach to automatic thesaurus construction for Chinese documents. An effective Chinese keyword extraction algorithm is first presented. Experiments showed that for each document an average of 33% keywords unknown to a lexicon of 123,226 terms could be identified by this algorithm. Of these unregistered words, only 8.3% of them are illegal. Keywords extracted from each document are further filtered for term association analysis. Association weights larger than a threshold are then accumulated over all the documents to yield the final term pair similarities. Compared to previous studies, this method speeds up the thesaurus generation process drastically. It also achieves a similar percentage level of term relatedness.

Suggested Citation

  • Yuen‐Hsien Tseng, 2002. "Automatic thesaurus generation for Chinese documents," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(13), pages 1130-1138, November.
    • Handle: RePEc:bla:jamist:v:53:y:2002:i:13:p:1130-1138
    DOI: 10.1002/asi.10146
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    Cited by:

    1. Yuen-Hsien Tseng & Ming-Yueh Tsay, 2013. "Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 503-528, May.
    2. Yuen-Hsien Tseng & Yu-I Lin & Yi-Yang Lee & Wen-Chi Hung & Chun-Hsiang Lee, 2009. "A comparison of methods for detecting hot topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(1), pages 73-90, October.

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