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[Demo] From to recommendations in social tagging sites

Sihem Amer-yahia 1 Alban Galland 1, 2 Julia Stoyanovich 1, 3 Cong yu 1 
2 GEMO - Integration of data and knowledge distributed over the web
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : We present, a scalable system for managing rec- ommendations for social tagging sites like seam- lessly incorporates various user behaviors into the recom- mendations and aims to recommend not only items of in- terest, but also other relevant information like interesting people and/or topics. Explanations are also provided so that users can obtain a better understanding of the recommenda- tions and decide which recommendations to pursue further. We discuss the technical challenges involved in character- izing different user behaviors and in efficiently computing recommendation explanations.
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Submitted on : Tuesday, September 28, 2010 - 2:09:31 PM
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Sihem Amer-yahia, Alban Galland, Julia Stoyanovich, Cong yu. [Demo] From to recommendations in social tagging sites. SIGMOD, Jun 2009, Vancouver, Canada. ⟨10.1145/1376616.1376766⟩. ⟨inria-00521708⟩



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