User and Document Group Approach of Clustering in Tagging Systems

In this paper, we propose a spectral cluster-ing approach for users and documents group modeling in order to capture the common preference and relatedness of users and doc-uments, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduc-tion of the time consuming in calculating the similarity for the recommender systems by se-lecting a centroid first, and then compare the inside item on behalf of each group