Hopfgartner, F. orcid.org/0000-0003-0380-6088 and Jose, J.M. (2010) Semantic User Profiling Techniques for Personalised Multimedia Recommendation. Multimedia Systems, 16 (4-5). pp. 255-274. ISSN 0942-4962
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer-Verlag 2010. This is an author produced version of a paper subsequently published in Multimedia Systems. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Long-term user profiling; Video annotation; Multimedia recommendation; Evaluation; User simulation; Semantic web technologies |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Oct 2018 09:30 |
Last Modified: | 19 Oct 2018 09:30 |
Published Version: | https://doi.org/10.1007/s00530-010-0189-6 |
Status: | Published |
Publisher: | Springer |
Refereed: | Yes |
Identification Number: | 10.1007/s00530-010-0189-6 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:136952 |