基于双向最大匹配和HMM的分词消歧模型  

Sense Disambiguation of Chinese Segmentation Based on Bi-direction Matching Method and HMM

作　　者：麦范金[1] 王挺[2] 

机构地区：[1]桂林工学院现代教育技术中心,桂林541004 [2]桂林工学院电子与计算机系,桂林541004

出　　处：《现代图书情报技术》2008年第8期37-41,共5页New Technology of Library and Information Service

基　　金：广西教育厅科研项目"基于语意理解的垃圾邮件处理模型研究"(项目编号:桂教科研2006[26]号)的研究成果之一

摘　　要：提出一种消减分词切分歧义的模型。利用正向和逆向最大匹配方法对中文文本信息进行分词,基于隐马尔科夫模型对两次最大匹配的分词结果进行对比消歧,得到较为精确的结果。整个过程分为歧义发现、歧义抽取、歧义消除3个过程。测试结果显示,该模型能有效地降低分词歧义引起的错误切分率。This paper puts forward a model which can eliminate sense ambiguity of Chinese segmentation. This model segments word based on MM and RMM at first. Then it compares the segmentation results with each other, and output a more accurate result for the segmentation. The process can be divided into three parts ： discovery, extraction and disambiguation. The test result shows that this model is able to reduce the error rate of segmentation, which is caused by the ambiguity of word segmentation.

关 键 词：分词 最大匹配 隐马尔科夫模型 歧义消减 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]