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A review on deep learning for recommender systems: challenges and remedies.

, , , and . Artif. Intell. Rev., 52 (1): 1-37 (2019)

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Shilling attack detection in binary data: a classification approach., , and . J. Ambient Intell. Humaniz. Comput., 11 (6): 2601-2611 (2020)On Binary Similarity Measures for Privacy-preserving Top-N Recommendations., , and . ICSOFT (1), page 299-304. SciTePress, (2010)Robustness analysis of arbitrarily distributed data-based recommendation methods., and . Expert Syst. Appl., (2016)A novel classification-based shilling attack detection approach for multi-criteria recommender systems., , and . Comput. Intell., 39 (3): 499-528 (June 2023)Robustness Analysis of Naïve Bayesian Classifier-Based Collaborative Filtering., and . EC-Web, volume 152 of Lecture Notes in Business Information Processing, page 202-209. Springer, (2013)Privacy-preserving SOM-based recommendations on horizontally distributed data., and . Knowl. Based Syst., (2012)Providing Naïve Bayesian Classifier-Based Private Recommendations on Partitioned Data., and . PKDD, volume 4702 of Lecture Notes in Computer Science, page 515-522. Springer, (2007)Privacy-Aware Detection of Shilling Profiles on Arbitrarily Distributed Recommender Systems., , and . IEEE Access, (2019)SOM-based recommendations with privacy on multi-party vertically distributed data., and . J. Oper. Res. Soc., 63 (6): 826-838 (2012)Deriving ratings from a private P2P collaborative scheme., and . KSII Trans. Internet Inf. Syst., 13 (9): 4463-4483 (2019)