Abstract
There is a need for personalised news video retrieval due to the explosion of news materials available through broadcast and other channels. In this work we introduce a semantic based user modeling technique to capture the users' evolving information needs. Our approach exploits the Linked Open Data Cloud to capture and organise users' interests. The organised interests are used to retrieve and recommend news stories to users. The system monitors user interaction with its interface and uses this information for capturing their evolving interests in the news. New relevant materials are fetched and presented to the user based on their interests. A user-centred evaluation was conducted and the results show the promise of our approach. © 2010 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Hopfgartner, F., & Jose, J. M. (2009). Semantic user modelling for personal news video retrieval. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5916 LNCS, pp. 336–346). https://doi.org/10.1007/978-3-642-11301-7_35
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