Comparative Research on Symmetric and Asymmetric Word Clustering Models
Yuexian Hou · Jisuanji gongcheng · 2009
Word clustering is one of important natural language processing issues in speech recognition and intelligent information retrieval,etc.This paper presents a symmetric clustering model based on mutual information.For the model not taking the order of words into account,it proposes a new asymmetric clustering model including two sub models,conditional clustering model and predictive clustering model.Experimental results on large scale data set show that compared with the symmetric clustering model,the asymmetric clustering model is a more effective one for clustering words.