This article proposes a new method to overcome the sparse data problem of the collaborative filtering models (CF models) by considering the homologous relationship …
Y Wang, J Deng, J Gao, P Zhang - Information Sciences, 2017 - Elsevier
In the neighborhood-based Collaborative Filtering (CF) algorithms, the user similarity has an important effect on the result of CF. In order to evaluate the user similarity comprehensively …
TN Duong, VD Than, TH Tran, QH Dang… - … on Information and …, 2018 - ieeexplore.ieee.org
Thanks to its successful application in recommendation systems, collaborative filtering (CF) technique has become one of the most popular research topic in data mining and …
In recent years, collaborative filtering (CF) techniques have become one of the most popularly used techniques for providing personalized services to users. CF techniques …
Collaborative Filtering (CF) approaches have been widely used in various applications of recommender systems. These methods are based on estimating the similarity between …
Memory-based methods for collaborative filtering predict new ratings by averaging (weighted) ratings between, respectively, pairs of similar users or items. In practice, a large …
W Wang, G Zhang, J Lu - International Journal of Intelligent …, 2015 - Wiley Online Library
Collaborative filtering (CF) is the most popular approach in personalized recommender systems. Although CF approaches have successfully been used and have the advantage in …
H Ji, J Li, C Ren, M He - Proceedings of 2013 IEEE …, 2013 - ieeexplore.ieee.org
Collaborative filtering (CF) based recommendation system, which can automatically predict unknown preference of a user to certain products and then generate meaningful …
K Choi, Y Suh - Knowledge-Based Systems, 2013 - Elsevier
As one of the collaborative filtering (CF) techniques, memory-based CF technique which recommends items to users based on rating information of like-minded users (called …