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篇名
A Model for Word Sense Disambiguation
作者 Li, Juanzi (Li, Juanzi)Huang, Chang-ning (Huang, Chang-ning)
中文摘要
Word sense disambiguation is one of the most difficult problems in natural language processing. This paper puts forward a model for mapping a structural semantic space from a thesaurus into a multi-dimensional, real-valued vector space and gives a word sense disambiguation method based on this mapping. The model, which uses an unsupervised learning method to acquire the disambiguation knowledge, not only saves extensive manual work, but also realizes the sense tagging of a large number of content words. Firstly, a Chinese thesaurus Cilin and a very large-scale corpus are used to construct the structure of the semantic space. Then, a dynamic disambiguation model is developed to disambiguate an ambiguous word according to the vectors of monosemous words in each of its possible categories. In order to resolve the problem of data sparseness, a method is proposed to make the model more robust. Testing results show that the model has relatively good performance and can also be used for other languages.
起訖頁 1-19
關鍵詞 Natural language processingWord sense disambiguationUnsupervised learningVector spaceLanguage modeling
刊名 中文計算語言學期刊  
期數 199908 (4:2期)
出版單位 中華民國計算語言學學會
該期刊-下一篇 Resolving Translation Ambiguity and Target Polysemy in Cross-Language Information Retrieval+
 

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