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Many of the recent algorithms have been developed to improve the various aspects of collaborative filtering recommender systems, however, most of them do not take the sectional data of users and items information or characteristic into account. This paper, we present a new improved collaborative filtering based on item similarity modified and item common ratings which take full advantage of the sectional...
Recommendation systems can help people to find interesting things and they are widely used in our life with the development of the Internet. Collaborative filtering technique has been proved to be one of the most successful techniques in recommendation systems in recent years. Poor quality is one major challenge in collaborative filtering recommender systems. Sparsity of source data set is the major...
Collaborative filtering recommendation system is a widely used method of providing recommendations using explicit ratings on items from users, which provides personalized recommendations on products or services to customers. However, the current research on recommendation has paid little attention to the use of time-related data in the recommendation process and the study on collaborative filtering...
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