Self-Adaptive User Profiles for Large-Scale Data Delivery

Push-based data delivery requires knowledge of user interests for making scheduling, bandwidthallocation, and routing decisions. Such information is maintained as user profiles. We propose a new incremental algorithm for constructing user profiles based on monitoring and user feedback. In contrast to earlier approaches, which typically represent profiles as a single weighted interest vector, we represent user profiles as multipleinterest vectors, whose number, size, and elements change adaptively based on user access behavior. This flexible approach allows the profile to more accurately represent complex user interests. Although there has been significant research on user profiles, our approach is unique in that it can be tuned to trade off profile complexity and quality. This feature, together with its incremental nature, makes our method suitable for use in large-scale information filtering applications such as push-based WWW page dissemination. We evaluate the method by experimenta...

• Type: Conference
• Year: 2000
• Where: ICDE
• Authors: C. Lee Giles, Michael J. Franklin, Ugur Çetintemel
• Keywords: Complex User Interests, Database, ICDE 2000, User Access Behavior, User Profiles