Multimedia Systems

, Volume 16, Issue 4, pp 255–274

Semantic user profiling techniques for personalised multimedia recommendation

Regular Paper

DOI: 10.1007/s00530-010-0189-6

Cite this article as:
Hopfgartner, F. & Jose, J.M. Multimedia Systems (2010) 16: 255. doi:10.1007/s00530-010-0189-6


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.


Long-term user profilingVideo annotationMultimedia recommendationEvaluationUser simulationSemantic web technologies

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Department of Computing ScienceUniversity of GlasgowGlasgowScotland, UK