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)

54607.pdf - Accepted Version



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
Additional Information:This research was supported by the European Commission under contract FP6-027122-SALERO. It is the view of the authors but not necessarily the view of the community.
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 Arts > School of Humanities > Information Studies
College of Science and Engineering > School of Computing Science
Journal Name:Multimedia Systems
ISSN (Online):1432-1882
Published Online:14 May 2010
Copyright Holders:Copyright © 2010 Springer-Verlag
First Published:First published in Multimedia Systems 16(4-5):255-274
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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