Semantic user profiling techniques for personalised multimedia recommendation

Hopfgartner, F. and Jose, J.M. (2010) Semantic user profiling techniques for personalised multimedia recommendation. Multimedia Systems, 16(4-5), pp. 255-274. (doi:10.1007/s00530-010-0189-6)

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Due to the explosion of news materials available through broadcast and other channels, there is an increasing need for personalised news video retrieval. In this work, we introduce a semantic-based user modelling technique to capture users’ evolving information needs. Our approach exploits implicit user interaction to capture long-term user interests in a profile. The organised interests are used to retrieve and recommend news stories to the users. In this paper, we exploit the Linked Open Data Cloud to identify similar news stories that match the users’ interest. We evaluate various recommendation parameters by introducing a simulation-based evaluation scheme.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Jose, Professor Joemon and Hopfgartner, Dr Frank
Authors: Hopfgartner, F., and Jose, J.M.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
College of Arts > School of Humanities > Information Studies
Journal Name:Multimedia Systems
Published Online:14 May 2010

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