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dc.contributor.advisorChan, Philip K.
dc.contributor.authorKim, Hyoung-Rae
dc.contributor.authorChan, Philip K.
dc.date.accessioned2013-11-05T20:18:34Z
dc.date.available2013-11-05T20:18:34Z
dc.date.issued2003-06-11
dc.identifier.citationKim, H., Chan, P.K. (2003). Improving learning implicit user interest hierarchy with variable length phrases (CS-2003-17). Melbourne, FL. Florida Institute of Technology.en_US
dc.identifier.otherCS-2003-17
dc.identifier.urihttp://hdl.handle.net/11141/124
dc.description.abstractA continuum of general to specific interests of a user called a user interest hierarchy (UIH) represents a user's interests at different abstraction levels. A UIH can be learned from a set of web pages visited by a user. In this paper, we focus on improving learning the UIH by adding phrases. We propose the VPF algorithm that can find variable length phrases without any user-defined parameter. To identify meaningful phrases, we examine various correlation functions with respect to well-known properties and other properties that we propose.en_US
dc.language.isoen_USen_US
dc.rightsCopyright held by authors.en_US
dc.titleImproving learning implicit user interest hierarchy with variable length phrasesen_US
dc.typeTechnical Reporten_US


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