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Much efforts have lately been concentrated on increasing the precision of recommendations following the Netflix Prize competition. Recently, many researchers and industries have noted that other factors like adequate presentation of the results can add more utility to a recommender system than slight improvement in the precision. In this paper, we suggest a(More)
The need for efficient decentralized recommender systems has been appreciated for some time, both for the intrinsic advantages of decentralization and the necessity of integrating recommender systems into P2P applications. On the other hand, the accuracy of recommender systems is often hurt by data sparsity. In this paper, we compare different decentralized(More)
The need for efficient decentralized recommender systems has been appreciated for some time, both for the intrinsic advantages of decentralization and the necessity of integrating recommender systems into existing P2P applications. On the other hand, the accuracy of recommender systems is often hurt by data sparsity. In this paper, we compare different(More)
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