Abstract
Ranking of resources is relevant in information retrieval systems to present optimally targeted results to initially issued queries. Traditional ranking approaches from the field of information retrieval are not always appropriate to be implemented in search engines based on semantics. Thus this paper proposes a customized ranking approach for multimedia resources based on semantic annotations which is based on the vector space model. An initial version of the ranking algorithm is evaluated and refinements are proposed which are again evaluated in an end user experiment.
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Bürger, T., Huber, S. (2011). Ranking of Semantically Annotated Media Resources. In: Declerck, T., Granitzer, M., Grzegorzek, M., Romanelli, M., Rüger, S., Sintek, M. (eds) Semantic Multimedia. SAMT 2010. Lecture Notes in Computer Science, vol 6725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23017-2_2
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DOI: https://doi.org/10.1007/978-3-642-23017-2_2
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