Clustering Method Based on Fuzzy Multisets for Web Pages and Customer Segments

Web log mining is the application of data mining techniques to Web log data repositories, in which clustering analysis is one of important Web usage mining techniques. Recently various clustering approaches have been developed for Web pages and customer segments clustering. However, most of them take user access frequency or Web page time duration as measurement of user navigation interest without taking into consideration such important factors as user preference, browsing context, etc. A novel clustering method based on fuzzy multisets is proposed to deal with the problemsin this paper. In proposed method, the fuzzy multiset isadopted to characterize userpsilas navigation behavior and toconstruct a multi fuzzy similar matrix to represent similarity between different userspsila browsing behavior, which can reflectwholly the interest of Web user with the Web page-click rate, Web page viewing time, user's preference and so on. And Web page clusters and customer segments are abstracted directly from the corresponding multi fuzzy similar matrix. Anillustrative example is given to show how the algorithms work.