A top-down fuzzy cross-level Web-mining approach

Web mining of browsing patterns including simple sequential patterns and sequential patterns with browsing times has been studied recently. However, most of these works focus on mining browsing patterns of Web pages directly. In this work, we introduce the problem of mining browsing patterns on cross-levels of a taxonomy comprised of Web pages. In addition, browsing time is considered and processed using fuzzy set concepts to form linguistic terms. The proposed algorithm thus discovers cross-level relevant browsing behavior from linguistic data and promotes the discovery of coarsened granularity of Web browsing patterns.