Page clustering based on text-link model and affinity propagation algorithm
基于文本—链接模型和近邻传播算法的网页聚类*

Regarding clustering research of Web pages, several kinds of clustering algorithms based on text-link model have been proposed. Among all the algorithms, the MS model is the most widely used. This article proposed the TMSL model to improve the shortage of MS model on its effectiveness and accuracy. New model compressed the space of word and link vector by transforming word into the word cluster , link vector into link cluster. Affinity propagation clustering algorithm substituted for traditional K-means algorithm in clustering of the Web pages. The experimental results verify that the proposed method has highly accuracy and effectiveness.