四种统计词义消歧模型的分析与比较

Analysis and comparison of 4 kinds of statistical word sense disambiguation models

综合考察了贝叶斯模型、决策树模型、向量空间模型、最大熵模型在汉语词义消歧上的应用,并对它们的消歧效果进行比较,为词义消歧模型的选择与应用奠定基础。

Many modeling methods corresponding to different machine learning methods have been used for computational linguistic problems.To determine an appropriate modeling method,and select an effective machine learning methods is most important for statistical word sense disambiguation.In this paper the Bayesian model,decision tree model,vector space model and maximum entropy are probed comprehensively,Their effects on Chinese word sense disambiguation are compared,in order to build foundation for selecting and applying word sense disambiguation models.