Fuzzy Co-clustering Algorithm for Weblog

Weblog co-clustering is an important research content of Weblog mining, which has ability to find out the users clusters and pages clusters simultaneously. Most of the proposed Weblog co-clustering algorithm use hard partition method to assign the users into its corresponding cluster. However, hard partition method make these clustering algorithm can not handle the clusters bond problem very well, which has significant influence for the clustering result quality. In this paper, a Fuzzy CO-clustering for Weblog (FCOW) algorithm is proposed to overcome the default of hard partition and improve the clustering results quality of Weblog co-clustering. In particularly, the underlying users model setPA={pa1,paK} is first found by using Hadamard product; and then, the rest users are assigned to its corresponding modelpak based on page subset to generate the co-clustering result {CSk, CPk}; Finally, the fuzzy membership of each user to its page clusterCPk is calculated and this information is used to do recommendation. Experimental results on five real world datasets show that FCOW has ability for improving the clustering quality of Weblog co-clustering.