An Efficient Method of Web Sequential Pattern Mining Based on Session Filter and Transaction Identification
Web sequential pattern mining is an important way to analyze the access behavior of web users. In this paper, the authors present an efficient method of web sequential pattern mining based on session filter and transaction identification. Different from traditional mining methods, they categorize the user sessions into human user sessions, crawler sessions and resource-download user sessions. Then they filter out the non-human user sessions, leaving the human user sessions for sequential pattern mining.