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汉语未登录词的词义知识表示及语义预测
引用本文:田元贺,刘 扬.汉语未登录词的词义知识表示及语义预测[J].中文信息学报,2016,30(6):26-34.
作者姓名:田元贺  刘 扬
作者单位:1. 北京大学 中国语言文学系,北京 100871; 2. 北京大学 计算语言学教育部重点实验室,北京 100871;
3. 北京大学 计算语言学研究所,北京 100871
基金项目:国家社科基金(16BYY137);国家重点基础研究发展计划资助项目(2014CB340504);国家社科基金(12&ZD119)
摘    要:在此前的汉语未登录词语义预测中,构词相关的知识一直被当做预测的手段,而没有被视为一种有价值的知识表示方式,该文在“语素概念”基础上,深入考察汉语的语义构词知识,给出未登录词的“多层面”的词义知识表示方案。针对该方案,该文采用贝叶斯网络方法,构建面向汉语未登录词的自动语义构词分析模型,该模型能有效预测未登录词的“多层面”的词义知识。这种词义知识表示简单、直观、易于拓展,实验表明对汉语未登录词的语义预测具有重要的价值,可以满足不同层次的应用需求。

关 键 词:未登录词  词义知识表示  语义预测  语义构词  />  

Lexical Knowledge Representation and Sense Prediction of Chinese Unknown Words
TIAN Yuanhe,LIU Yang.Lexical Knowledge Representation and Sense Prediction of Chinese Unknown Words[J].Journal of Chinese Information Processing,2016,30(6):26-34.
Authors:TIAN Yuanhe  LIU Yang
Affiliation:1. Department of Chinese Language and Literature, Peking University, Beijing 100871, China;
2. Key Laboratory of Computational Linguistics Ministry of Education, Peking University, Beijing 100871, China;
3. Institute of Computational Linguistics, Peking University, Beijing 100871, China
Abstract:In the previous researches in sense prediction of Chinese unknown words, the lexical knowledge related to word-formation has been used but not regarded as a valuable form of knowledge representation. This paper, on the basis of the morphemic concepts, provides a multi-level solution to knowledge representation of Chinese unknown words. A model based on Bayesian network is also constructed to analyze semantic word-formation of Chinese unknown words, effectively predicting the multi-level lexical knowledge of Chinese unknown words. This kind of lexical knowledge representation is simple, intuitive and easy to expand. Experimental results show that, this knowledge representation is of important value in sense guessing of Chinese unknown words, and can meet the application needs on different levels.
Keywords:Chinese unknown words  lexical knowledge representation  sense prediction  semantic word formation
        
        
        
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