This paper presents efficient clustering with side information using probabilistic latent Semantic indexing. Meta information is available in many texts mining application. It may be useful or sometimes it is a risky approach to add side information. The aim of this work is to resolve clustering problem, for data mining problems, in which auxiliary information is available, to enhance the extraction of text document. The work proposed an approach, Probabilistic Latent Semantic Indexing, which gives more efficiency by considering class labels and also will be applicable for large number of clusters. The goal of this work is to utilize side information available with the documents for clustering, to improve the efficiency of the clusters and also to reduce the time required to form clusters.

Text Mining, Side information, Clustering, LSI, Probabilistic Latent Semantic Indexing

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