As the most successful recommendation technology, the core idea of traditional collaborative filtering algorithm is to calculate user similarity or item similarity from users'ratings and then to predict ratings and recommend items based on similar users' ratings or similar items'ratings. In real applications, however, there exists a problem of Data Sparsity in which most of users will only give a few ratings. In such a situation, traditional collaborative filtering algorithm cannot produce satisfactory resu...
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