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Rule Learning with Probabilistic Smoothing.

, , , , and . DaWaK, volume 5691 of Lecture Notes in Computer Science, page 428-440. Springer, (2009)

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Deep Sequential Modeling for Recommendation., , , and . SEBD, volume 2400 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)A Cloud-Based Prediction Framework for Analyzing Business Process Performances., , , and . CD-ARES, volume 9817 of Lecture Notes in Computer Science, page 63-80. Springer, (2016)Experimenting and Assessing a Probabilistic Business Process Deviance Mining Framework Based on Ensemble Learning., , , and . ICEIS (Revised Selected Papers), volume 321 of Lecture Notes in Business Information Processing, page 96-124. Springer, (2017)A Block Mixture Model for Pattern Discovery in Preference Data., , and . ICDM Workshops, page 1100-1107. IEEE Computer Society, (2010)Mining Predictive Process Models out of Low-level Multidimensional Logs., , and . CAiSE, volume 8484 of Lecture Notes in Computer Science, page 533-547. Springer, (2014)A multi-view multi-dimensional ensemble learning approach to mining business process deviances., , , and . IJCNN, page 3809-3816. IEEE, (2016)High Quality True-Positive Prediction for Fiscal Fraud Detection., , , , , , , , and . ICDM Workshops, page 7-12. IEEE Computer Society, (2009)An Approach to the Discovery of Accurate and Expressive Fix-Time Prediction Models., , and . ICEIS (Revised Selected Papers), volume 227 of Lecture Notes in Business Information Processing, page 108-128. Springer, (2014)A Multi-view Learning Approach to the Discovery of Deviant Process Instances., , , and . OTM Conferences, volume 9415 of Lecture Notes in Computer Science, page 146-165. Springer, (2015)Using Deep Learning and Data Integration for Accurate Rainfall Estimates., , , and . ERCIM News, (2020)