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 …
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 …
In recent years, collaborative filtering (CF) techniques have become one of the most popularly used techniques for providing personalized services to users. CF techniques …
KJ Kim, HC Ahn - Journal of Information Technology Applications …, 2009 - koreascience.kr
Collaborative filtering (CF) has been a very successful approach for building recommender system, but its widespread use has exposed to some well-known problems including …
NN Liu, M Zhao, Q Yang - Proceedings of the 18th ACM conference on …, 2009 - dl.acm.org
A central goal of collaborative filtering (CF) is to rank items by their utilities with respect to individual users in order to make personalized recommendations. Traditionally, this is often …
Recommender systems are a valuable means for online users to find items of interest in situations when there exists a large set of alternatives. Collaborative Filtering (CF) is a …
Recommender systems base their operation on past user ratings over a collection of items, for instance, books, CDs, etc. Collaborative filtering (CF) is a successful recommendation …
With the rapid development and application of the mobile Internet, huge amounts of user data are generated and collected every day. How to take full advantages of these ubiquitous …
Recommender systems are widely used for automatic personalization of information on web sites and information retrieval systems. Collaborative Filtering (CF) is the most popular …