A Chinese Word Clustering Method Using Latent Dirichlet Allocation and K-means
Lin Qiu, Jungang Xu · 2013
Word clustering is a popular research issue in the field of natural language processing.In this paper, Latent Dirichlet Allocation algorithm is used to extract the topics from nouns in the text, and the highest probability noun of each topic is selected as the centroids of the k-means algorithm.Experimental results show that this method can get better effects than the graph-based word clustering algorithms using a web search engine.