News-oriented automatic Chinese keyword indexing
Pages 92 - 97
Abstract
In our information era, keywords are very useful to information retrieval, text clustering and so on. News is always a domain attracting a large amount of attention. However, the majority of news articles come without keywords, and indexing them manually costs highly. Aiming at news articles' characteristics and the resources available, this paper introduces a simple procedure to index keywords based on the scoring system. In the process of indexing, we make use of some relatively mature linguistic techniques and tools to filter those meaningless candidate items. Furthermore, according to the hierarchical relations of content words, keywords are not restricted to extracting from text. These methods have improved our system a lot. At last experimental results are given and analyzed, showing that the quality of extracted keywords are satisfying.
References
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{Frank 1999} Frank E., Paynter G. W., Witten I. H., Gutwin C., and Nevill-Manning C. G., Domain-specific keyphrase extraction, Proc. Sixteenth International Joint Conference on Artificial Intelligence, Morgan Kaufmann Publishers, San Francisco, CA, 1999, pp. 668--673.
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{Lai 2002} Yu-Sheng Lai, Chung-Hsien Wu, Meaningful term extraction and discriminative term selection in text categorization via unknown-word methodology, ACM Transactions on Asian Language Information Processing (TALIP), Vol.1, No.1, March 2002, pp. 34--64.
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{Liu 1998} Liu Ting, Wu Yan, Wang Kaizhu, An Chinese Word Automatic Segmentation System Based on String Frequency Statistics Combined with Word Matching, Journal of Chinese Information Processing, Vol.12, No.1, 1998, pp. 17--25.
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{Ong 1999} T. Ong and H. Chen, Updateable PAT-Tree Approach to Chinese Key Phrase Extraction Using Mutual Information: A Linguistic Foundation for Knowledge Management, Proceedings of the Second Asian Digital Libaray Conference, Taipei, Taiwan, Novemeber 8-9, 1999.
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{Witten 1999} Witten I. H., Paynter G. W., Frank E., Gutwin C., and Nevill-Manning C. G., KEA: Practical automatic keyphrase extraction, Proc. DL '99, 1999, pp. 254--256.
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Association for Computational Linguistics
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Published: 11 July 2003
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