Network User Interest Pattern Mining Based on Entropy Clustering Algorithm

This paper proposed an automatic clustering algorithm based on entropy for discovering the interest pattern over users' web log. We introduced the information entropy on the basis of clustering algorithm. Compared with traditional clustering algorithms, our method does not require any parameters specified by the end user. Meanwhile, it can discover the clusters in arbitrary shape and size. Experimental results over real-world dataset have fully demonstrated the advantages of our algorithm, which is effective in the problem of high-dimensional and non-informative priors pattern recognition.