Data mining techniques for portal participants profiling

Abstract

Recently, a large number of virtual learning communities appeared in the Web, however,keeping them up occurs to be problematic and information accessibility is one of the factors thatmay influence their sustainability. This feature may be achieved by dividing users into groupsaccording to their information needs and by adapting properly the portal contents. In the paperapplication for data mining algorithms, for finding patterns together with different groups ofpreferences is considered. We base our research on the data contained in log files. Combination ofsequential pattern mining and clustering techniques is proposed. We describe the data preparationprocess. The experiments conducted for real data log files are discussed