An Efficient Approach for Analyzing User Behaviors in a Web-Based Training Environment

Mining frequent traversal patterns is to discover the consecutive reference paths traversed by a sufficient number of users from Web logs in a Web environment where users can travel from one object to another through the corresponding hyperlinks. Previous approaches for mining frequent traversal patterns only consider the forward references, such that the information about backward references will be lost. In this paper, we propose an efficient algorithm to discover the non-simple frequent traversal patterns. The non-simple frequent traversal patterns include forward and backward references, and are used to suggest potentially interesting traversal path to the users, which are useful, especially, in a Web-based training environment. The experimental results show that the discovered patterns can present the complete browsing paths traversed by most of the users and our algorithm outperforms other algorithms in discovered information and execution times.