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Internet and E-Commerce are becoming an integral part of everyday life as we accumulate more and more knowledge that demands for some personalized recommendation technology. Collaborative filtering recommendation is the most successful personalized recommendation algorithm among current technologies. The paper suggests the two-phase clustering-based collaborative filtering algorithm. which not only...
Personalized recommendation systems can help people to find interesting things and they are widely used in our life. Poor quality is one major challenge in collaborative filtering recommender systems. Sparsity of source data set is the major reason causing the poor quality. Aiming at the problem of data sparsity for collaborative filtering, a novel rough set and fuzzy clustering based collaborative...
Collaborative filtering technique has been proved to be one of the most successful techniques in recommendation systems in recent years. However, most existing collaborative filtering based recommendation systems suffered from its shortage in scalability as their calculation complexity increased quickly both in time and space when the record in user database increases. So, a new collaborative filtering...
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