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Online and offline classification of traces of event logs on the basis of security risks.

, , , and . J. Intell. Inf. Syst., 50 (1): 195-230 (2018)

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Business Process Deviance Mining., and . Encyclopedia of Big Data Technologies, Springer, (2019)Pushing More AI Capabilities into Process Mining to Better Deal with Low-Quality Logs., and . Business Process Management Workshops, volume 362 of Lecture Notes in Business Information Processing, page 5-11. Springer, (2019)An approach for the extensional integration of data sources with heterogeneous representation formats., , and . Data Knowl. Eng., 45 (3): 291-331 (2003)Exploiting structural similarity for effective Web information extraction., , , , and . Data Knowl. Eng., 60 (1): 222-234 (2007)Coclustering Multiple Heterogeneous Domains: Linear Combinations and Agreements., , and . IEEE Trans. Knowl. Data Eng., 22 (12): 1649-1663 (2010)Combining Different Data Mining Techniques to Improve Data Analysis., , and . FQAS, volume 7 of Advances in Soft Computing, page 455-464. Physica-Verlag Heidelberg New York, A Springer-Verlag Company, (2000)Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction., , , and . Data Knowl. Eng., 70 (12): 1005-1029 (2011)Deviance-Aware Discovery of High-Quality Process Models., , , and . Int. J. Artif. Intell. Tools, 27 (7): 1860009:1-1860009:27 (2018)On the Interpretation of Traces of Low Level Events in Business Process Logs., , , , and . SEBD, volume 2161 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)Process Discovery via Precedence Constraints., , and . ECAI, volume 242 of Frontiers in Artificial Intelligence and Applications, page 366-371. IOS Press, (2012)