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A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data (Extended Abstract)., , and . SEBD, page 239-246. (2011)A Transactional Approach to Associative XML Classification by Content and Structure., , and . KDIR, page 104-113. SciTePress, (2011)Deep Sequential Modeling for Recommendation., , , and . SEBD, volume 2400 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)The DAEDALUS framework: progressive querying and mining of movement data., , , , , , , , and . GIS, page 52. ACM, (2008)Enforcing Interaction and Cooperation in Content-Based Web3.0 Applications., , , , and . APWeb, volume 7235 of Lecture Notes in Computer Science, page 472-483. Springer, (2012)Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data., , , and . SDM, page 1035-1046. SIAM / Omnipress, (2012)Predicting Temporal Activation Patterns via Recurrent Neural Networks., , and . ISMIS, volume 11177 of Lecture Notes in Computer Science, page 347-356. Springer, (2018)Sequential Variational Autoencoders for Collaborative Filtering., , , and . CoRR, (2018)Machine learning methods for generating high dimensional discrete datasets., , , , and . WIREs Data Mining Knowl. Discov., (2022)Unbiasing Collaborative Filtering for Popularity-Aware Recommendation (Discussion Paper)., , , , and . SEBD, volume 2994 of CEUR Workshop Proceedings, page 450-457. CEUR-WS.org, (2021)