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An Evidential Collaborative Filtering Dealing with Sparsity Problem and Data Imperfections.

, , and . ISDA (2), volume 941 of Advances in Intelligent Systems and Computing, page 521-531. Springer, (2018)

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Towards more trustworthy predictions: A hybrid evidential movie recommender system., , and . J. Univers. Comput. Sci., 28 (10): 1003-1029 (2022)An Evidential Collaborative Filtering Dealing with Sparsity Problem and Data Imperfections., , and . ISDA (2), volume 941 of Advances in Intelligent Systems and Computing, page 521-531. Springer, (2018)Handling Uncertainty in Recommender Systems under the Belief Function Theory.. IJCAI, page 5761-5762. ijcai.org, (2018)Towards a Hybrid User and Item-Based Collaborative Filtering Under the Belief Function Theory., , and . IPMU (1), volume 853 of Communications in Computer and Information Science, page 395-406. Springer, (2018)Assessing Items Reliability for Collaborative Filtering Within the Belief Function Framework., , and . ICDEc, volume 290 of Lecture Notes in Business Information Processing, page 208-217. Springer, (2017)An Evidential Clustering for Collaborative Filtering Based on Users' Preferences., , and . MDAI, volume 11676 of Lecture Notes in Computer Science, page 224-235. Springer, (2019)Evidential Item-Based Collaborative Filtering., , and . KSEM, volume 9983 of Lecture Notes in Computer Science, page 628-639. (2016)An Evidential Collaborative Filtering Approach Based on Items Contents Clustering., , and . BELIEF, volume 11069 of Lecture Notes in Computer Science, page 1-9. Springer, (2018)Joining Items Clustering and Users Clustering for Evidential Collaborative Filtering., , and . IDEAL (1), volume 11871 of Lecture Notes in Computer Science, page 310-318. Springer, (2019)Improving the Trustworthiness of Recommendations in Collaborative Filtering under the Belief Function Framework.. RecSys, page 421-425. ACM, (2017)