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The Potential of Bookmark Based User Profiles

Driven by the explosive growth of information available online, the World-Wide-Web is currently witnessing a trend towards personalized information access. As part of this trend, numerous personalized news services are emerging. The goal of this project is to develop a prototype algorithm for using bookmarks to develop a personal profile. Ultimately, we imagine this might be used to construct a personalized RSS reader for reading news online. A reader returns a large number of news stories. To increase user satisfaction it is useful to rank them to bring the most interesting to the fore. This ranking is done by implementing a personalized profile. One way to create such a profile might be to extract it from users bookmarks. In this paper, we describe a process for learning user interest from bookmarks and present an evaluation of its effectiveness. The goal is to utilize a user profile based on bookmarks to personalize results by filtering and re-ranking the entries returned from a set of user defined feeds.

Identiferoai:union.ndltd.org:PITT/oai:PITTETD:etd-05042010-125657
Date12 May 2010
CreatorsYazagan, Asli
ContributorsMichael B. Spring, C. Michael Lewis, Stephen C. Hirtle
PublisherUniversity of Pittsburgh
Source SetsUniversity of Pittsburgh
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.library.pitt.edu/ETD/available/etd-05042010-125657/
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