Using Ontologies to Discover Domain-Level Web Usage Profiles

Abstract

Usage patterns discovered through Web usage mining are effective in capturing item-to-item and user-to-user relationships and similarities at the level of user sessions. Without the benefit of deeper domain knowledge, such patterns provide little insight into the underlying reasons for which such items or users are grouped together. This can lead to a number of important shortcomings in personalization systems based on Web usage mining or collaborative filtering. For example, if a new item is recently added to the Web site, it is not likely that the pages associated with the item would be a part of any of the discovered patterns, and thus these pages cannot be recommended. Keyword-based content-filtering approaches have been used to enhance the effectiveness of collaborative filtering systems by focusing on content similarity among items or pages. These approaches, however, are incapable of capturing more complex relationships at a deeper semantic level based on different types of attributes associated with structured objects. This paper represents work-in-progress towards creating a general framework for using domain ontologies to automatically characterize usage profiles containing a set of structured Web objects. Our motivation is to use this framework in the context of Web personalization, going beyond pageor item-level constructs, and using the full semantic power of the underlying ontology.