Flexible User Profiles for Large Scale Data Delivery

dc.contributor.authorCetintemel, Uguren_US
dc.contributor.authorFranklin, Michael J.en_US
dc.contributor.authorGiles, C. Leeen_US
dc.date.accessioned2004-05-31T22:56:41Z
dc.date.available2004-05-31T22:56:41Z
dc.date.created1999-03en_US
dc.date.issued1999-03-30en_US
dc.description.abstractPush-based data delivery requires knowledge of user interests for making scheduling, bandwidth allocation, 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 using multiple interest clusters, 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. The approach can be tuned to trade off profile complexity and effectiveness, making it suitable for use in large-scale information filtering applications such as push-based WWW page dissemination. We evaluate the method by experimentally investigating its ability to categorize WWW pages taken from Yahoo! categories. Our results show that the method can provide high retrieval effectiveness with modest profile sizes and can effectively adapt to changes in users' interests. Also cross-referenced as UMIACS-TR-99-18en_US
dc.format.extent245550 bytes
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/1903/1002
dc.language.isoen_US
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_US
dc.relation.isAvailableAtUniversity of Maryland (College Park, Md.)en_US
dc.relation.isAvailableAtTech Reports in Computer Science and Engineeringen_US
dc.relation.isAvailableAtUMIACS Technical Reportsen_US
dc.relation.ispartofseriesUM Computer Science Department; CS-TR-4005en_US
dc.relation.ispartofseriesUMIACS; UMIACS-TR-99-18en_US
dc.titleFlexible User Profiles for Large Scale Data Deliveryen_US
dc.typeTechnical Reporten_US

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