Demo From to recommendations in social tagging sitesReport as inadecuate

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1 Yahoo! Labs New York 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 3 Columbia University New York

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.

Author: Sihem Amer-Yahia - Alban Galland - Julia Stoyanovich - Cong Yu -



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