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Lazy and Eager Relational Learning Using Graph-Kernels.

, , , and . SLSP, volume 8791 of Lecture Notes in Computer Science, page 171-184. Springer, (2014)

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Inducing Probabilistic Relational Rules from Probabilistic Examples., , , , and . IJCAI, page 1835-1843. AAAI Press, (2015)Combining Text Mining Techniques for QA4MRE 2013., and . CLEF (Working Notes), volume 1179 of CEUR Workshop Proceedings, CEUR-WS.org, (2013)Data Mining, Interactive Semantic Structuring, and Collaboration: A Diversity-aware Method for Sense-making in Search., , and . LivingWeb@ISWC, volume 515 of CEUR Workshop Proceedings, CEUR-WS.org, (2009)Towards Contextual, Cost-Efficient Predictive Maintenance in Heavy-Duty Trucks., , and . IDA (2), volume 14642 of Lecture Notes in Computer Science, page 260-267. Springer, (2024)A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes., , , and . BNAIC/BENELEARN, volume 2491 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)An unsupervised methodology for online drift detection in multivariate industrial datasets., and . ICDM (Workshops), page 392-399. IEEE, (2020)Multi-view contextual performance profiling in rotating machinery., , , , and . ICPHM, page 343-350. IEEE, (2023)Relational Regularization and Feature Ranking., , and . SDM, page 650-658. SIAM, (2014)kLogNLP: Graph Kernel-based Relational Learning of Natural Language., , , , and . ACL (System Demonstrations), page 85-90. The Association for Computer Linguistics, (2014)Process mining on machine event logs for profiling abnormal behaviour and root cause analysis., , and . Ann. des Télécommunications, 75 (9-10): 563-572 (2020)