Results 21 to 30 of about 201,081 (282)
An Improved Dynamic Collaborative Filtering Algorithm Based on LDA
IEEE Access, 2021 Currently, available collaborative filtering (CF) algorithms often utilize user behavior data to generate recommendations. The similarity calculation between users is mostly based on the scores, without considering the explicit attributes of the users ...
Meng Di-Fei +3 more
doaj +1 more source
Content-boosted Matrix Factorization Techniques for Recommender Systems [PDF]
, 2013 Many businesses are using recommender systems for marketing outreach. Recommendation algorithms can be either based on content or driven by collaborative filtering.
Nguyen, Jennifer, Zhu, Mu
core +1 more source
Active Collaborative Filtering
CoRR, 2012 Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of online and interactive CF: given the current ratings associated with a user, what queries (new ratings) would most improve the quality of the recommendations made?
Craig Boutilier +2 more
openaire +3 more sources
Robust collaborative filtering [PDF]
Proceedings of the 2007 ACM conference on Recommender systems, 2007 The widespread deployment of recommender systems has lead to user feedback of varying quality. While some users faithfully express their true opinion, many provide noisy ratings which can be detrimental to the quality of the generated recommendations.
Bhaskar Mehta +2 more
openaire +1 more source
Causal Collaborative Filtering
Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval, 2023 Accepted by the 2023 ACM SIGIR International Conference on Theory of Information ...
Shuyuan Xu +5 more
openaire +2 more sources
Classification and Comparison of the Hybrid Collaborative Filtering Systems [PDF]
International Journal of Research in Industrial Engineering, 2017 Recommender systems have become fundamental applications in overloaded information domains like e-commerce. These systems aim to provide users with suggestions about items that are likely to be of their interest.
F. S. Gohari, M.J. Tarokh
doaj +1 more source
Statistical analysis of $k$-nearest neighbor collaborative recommendation [PDF]
, 2010 Collaborative recommendation is an information-filtering technique that attempts to present information items that are likely of interest to an Internet user.
Biau, Gérard +2 more
core +5 more sources
Collaborative Filtering Bandits [PDF]
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016 The 39th SIGIR (SIGIR 2016)
Shuai Li 0011 +2 more
openaire +2 more sources
Collaborative Filtering Based on Gaussian Mixture Model and Improved Jaccard Similarity
IEEE Access, 2019 The recommender systems play an important role in our lives, since it can quickly help users find what they are interested in. Collaborative filtering has become one of the most widely used algorithms in recommender systems due to its simplicity and ...
Hangyu Yan, Yan Tang
doaj +1 more source
QoS Prediction of Web Service Based on Community Detection [PDF]
Jisuanji gongcheng, 2019 Traditional collaborative filtering methods face many problems such as data sparsity,cold start and noise influences when predicting unknown Quality of Service(QoS) values.Therefore a new QoS prediction method based on community discovery is proposed ...
LU Beini,DU Yugen
doaj +1 more source