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Effect of Different Implicit Social Networks on Recommending Research Papers
2016
Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization - UMAP '16
Combining social network information with collaborative filtering recommendation algorithms has successfully reduced some of the drawbacks of collaborative filtering and increased the accuracy of recommendations. However, all approaches in the domain of research paper recommendation have used explicit social relations that users have initiated which has the problem of low recommendation coverage. We argued that the available data in social bookmarking Web sites such as CiteULike or Mendeley
doi:10.1145/2930238.2930293
dblp:conf/um/AlotaibiV16
fatcat:2sps432xlbatjolsxukeyppzh4