Papers in this group tagged with "recommendation systems"
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As part of the Linking Open Data initiative many (community) platforms have made their data freely available in recent years. In these systems valuable information from the music domain can be found. We use this data for contentbased music…
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Information overload on the Internet motivates the need for filtering tools. Recommender systems play a significant role in such a scenario, as they provide automatically generated suggestions. In this paper, we propose a novel recommendation…
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We present our recent work on recommending personalized news articles to users based on implicit collected feedback and large scale semantic datasets. Our personalized recommendation application SERUM exploits the fact that semantically linked and…
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seevl mines music connections from the Web to bring con- text, search and discovery for the music you like, directly within your favorite applications.We rely on the latest SemanticWeb / Linked Data technologies in order to (1) aggregate, interlink…