该本的多词串抽取是自然语言处理领域一项重要的研究内容。该文提出了一种多类别C-value(Multi-Class C-value)方法,利用多词串在不同领域的分布信息改善领域相关的多词串抽取的性能。在汽车、科技和旅行三个领域的数据上进行实验,评价多词串的准确率,在top-100级别上,较传统的C-value方法在三个领域中分别提高了12、12和13个百分点。实验结果验证了方法的有效性。
Abstract
Automatic multi-word terms extraction attracts more and more attention in the research of natural language processing. This paper proposes a Multi-Class C-value method, which uses the distribution of multi-word terms in different domains, to improve the performance of multi-word terms extraction. In the experiment with the data of automobile, technology and trip, the precisions of top 100 multi-word terms are 12%, 12% and 13% higher than the clssical C-value method in three domains respectively.
Key wordscomputer application; Chinese information processing; multi-word terms extraction; Multi-Class C-value;domain information
关键词
计算机应用 /
中文信息处理 /
多词串抽取 /
多类别C-value /
领域信息
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Key words
computer application /
Chinese information processing /
multi-word terms extraction /
Multi-Class C-value /
domain information
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参考文献
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[6] Beatrice Daille,Eric Gaussier,Jean-Marc Lange.Towards automatic extraction of monolingual and bilingual terminology[C]//Proceedings of the 15th International Conference on Computational Linguistics.Morristown,NJ,USA: Association for Computational Linguistics,1994: 515-521.
[7] John S. Justeson,Slava M. Katz.Technical terminology: some linguistic properties and an algorithm for identication in text[J]. Natural Language Engineering, 1(1):9-27, 1995.
[8] Chantal Enguehard,Laurent Pantera. Automatic natural acquisition of a terminology[J]. Journal of Quantitative Linguistics,1994,2(1): 27-32.
[9] KT Frantzi,S Ananiadou.The C-Value/NCValue domain independent method for multi-word term extraction[J]. Journal of Natural Language Processing,1999,6(3): 145-179.
[10] 朱靖波,陈文亮.基于领域知识的文本分类[J].东北大学学报,2005,26(8): 733-735.
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脚注
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基金
国家自然科学基金资助项目(60873091);辽宁省自然科学基金资助项目(20072032);沈阳市科学技术计划资助项目(1081235-1-00)
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