Efficient mining of utility-based web path traversal patterns

Mining useful Web path traversal patterns is a very important research issue in Web technologies. Knowledge about the frequent Web path traversal patterns enables us to discover the most interesting Websites traversed by the users. However, considering only the binary (presence/absence) occurrences of the Websites in the Web traversal paths, real world scenarios may not be reflected. Therefore, if we consider the time spent by each user as a utility value of a website, more interesting web traversal paths can be discovered. In this paper, we propose a novel algorithm for utility-based web path traversal pattern mining. Our extensive experimental results show that our algorithm outperforms the existing algorithm.