基于双语词汇Web间接关联的无指导译文消歧  

Unsupervised Translation Disambiguation Based on Web Indirect Association of Bilingual Word

作　　者：刘鹏远[1] 赵铁军[2] 

机构地区：[1]北京大学计算语言学研究所,北京100871 [2]哈尔滨工业大学计算机科学与技术学院,黑龙江哈尔滨150001

出　　处：《软件学报》2010年第4期575-585,共11页Journal of Software

基　　金：国家自然科学基金No.60903063;国家重点基础研究发展计划(973)No.2004CB318102~~

摘　　要：为解决困扰词义消歧及译文消歧任务中存在的数据稀疏及知识获取问题,提出一种利用双语词汇Web间接关联的完全无指导消歧方法.首先做出词汇歧义可由双语词汇的间接关联度决定的假设,为译文消歧提供了一种新的知识.在此基础上,对4种常用计算间接关联的方法进了改造并定义了双语词汇Web间接关联.随后进行基于Web的词汇消歧知识获取并设计了3种消歧决策方法.最后,在国际语义评测SemEval-2007中的Multilingual Chinese English Lexical Sample Task测试集进行了测试.该方法的Pmar值为44.4%,超过了该评测上最好的无指导系统的结果.To solve the problems of data sparseness and knowledge acquisition in translation disambiguation and WSD （word sense disambiguation）, this paper introduces a fully unsupervised method, which is based on Web mining and Web indirect association of bilingual words. It provides new knowledge of translation disambiguation. It assumes that word sense can be determined by indirect association of bilingual words. Based on Web, this paper revises four common methods of indirect association, and designs three decision methods. These methods are evaluated on a gold standard Multilingual Chinese English Lexical Sample Task dataset of SemEval- 2007. The experimental results show that the model gets the state-of-the-art results （Pmar=44.4%） and outperforms the best system in SemEval-2007.

关 键 词：词义消歧 无指导译文消歧 Web间接关联 知识获取 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]