Results 31 to 40 of about 46,255 (310)
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
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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
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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
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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
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Neural Collaborative Filtering [PDF]
Proceedings of the 26th International Conference on World Wide Web, 2017 10 pages, 7 ...
Xiangnan He 0001 +5 more
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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
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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
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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
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Rating Prediction Quality Enhancement in Low-Density Collaborative Filtering Datasets
Big Data and Cognitive Computing, 2023 Collaborative filtering has proved to be one of the most popular and successful rating prediction techniques over the last few years. In collaborative filtering, each rating prediction, concerning a product or a service, is based on the rating values ...
Dionisis Margaris +3 more
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Slope One Predictors for Online Rating-Based Collaborative Filtering [PDF]
, 2005 Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with predictors of the form f(x) = x + b, which precompute the average difference ...
Daniel Lemire +3 more
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