Text clustering is an important field of text mining research branch, is the clustering in the field of text processing applications. In this paper, based on vector space model for text clustering process to do a more in-depth discussion and summary, the use of the text corpus, based on data mining tools to study and realize the document clustering process. This paper shows the ideas and text clustering process, reviewed the existing text clustering results of the field, citing the field of document clustering in the feature representation, feature extraction and other aspects of basic research. In addition, the paper reviews the existing text clustering algorithm, as well as common text clustering validity. In the study has been based on the results, we use 20 Newsgroup corpus, for the vector space representation model, in the WEKA open source data mining platform to achieve a text preprocessing and k-means clustering algorithm, and according to the actual clustering effect to the tex

基于WEKA平台的文本聚类研究与实现.pdf

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