Web Usage Mining (WUM) integrates the techniques of two popular research fields - Data Mining and the Internet. By analyzing the potential rules hidden in web logs, WUM helps personalize the delivery of web content and improve web design, customer satisfaction and user navigation through pre-fetching and caching. This paper introduces two prevalent data mining algorithms - FPgrowth and PrefixSpan into WUM and they are applied in a real business case. Maximum Forward Path (MFP) is also used in the web usage mining model during sequential pattern mining along with PrefixSpan so as to reduce the interference of "false visit" caused by browser cache and raise the accuracy of mining frequent traversal paths. Detailed analysis and application on the corresponding results are discussed.
Wang, Hengshan; Yang, Cheng; and Zeng, Hua
"Design and Implementation of a Web Usage Mining Model Based On Upgrowth and Preflxspan,"
Communications of the IIMA: Vol. 6
, Article 10.
Available at: https://scholarworks.lib.csusb.edu/ciima/vol6/iss2/10