PPT-Decomposed Process Mining: The ILP Case

Eric Verbeek and Wil van der Aalst A Problem department of mathematics and computer science PAGE 1 292014 A Solution department of mathematics and computer science PAGE 2 292014. Abstract. Although most business processes change over time, contemporary process mining techniques tend to . analyze. these processes as if they are in a steady state. Processes may change suddenly or gradually. The drift may be periodic (e.g., because of seasonal influences) or one-of-a-kind (e.g., the effects of new legislation). For the process management, it is crucial to discover and understand such concept drifts in processes.. Sensitive Processes through Process . Mining. Jorge . Munoz-Gama . and. . Isao . Echizen. Insuring . Sensitive Processes through Process . Mining. Insuring Scenario. Insurance Company. 3. Clients. Discovering Business Rules From Event Logs. Marlon Dumas. University of Tartu, Estonia. With contributions from . Luciano. . García-Bañuelos. , . Fabrizio. . Maggi. & . Massimiliano. de . Leoni. Discovering Business Rules From Event Logs. Marlon Dumas. University of Tartu, Estonia. With contributions from . Luciano. . García-Bañuelos. , . Fabrizio. . Maggi. & . Massimiliano. de . Leoni. www.pwc.com. TU/e, .  . September 17. th. , 2015. Zbigniew ‘Zibi’ Paszkiewicz, Ph.D.. Manager. System and Process Assurance. Data Assurance Group. zbigniew.paszkiewicz@be.pwc.com. Purpose. Process mining @ PwC. Tiffany. . Chiu,. . Yunsen. Wang. . and. . Miklos. . Vasarhelyi. Rutgers 18th Fraud Seminar, December 7. th. This paper aims at providing a framework on how process mining can be applied to identify fraud schemes and assessing the riskiness of business processes. . Marlon Dumas. University of Tartu, Estonia. With contributions from . Luciano. . García-Bañuelos. , . Fabrizio. . Maggi. & . Massimiliano. de . Leoni. Theory Days, . Saka. , 2013. Business Process Mining. Zhenqi Hu. 1,2 . 胡振琪. 1,2 . Wu Xiao. 1,2 . 肖武. 1,2 . 1.Institute of Land Reclamation & Ecological Restoration. China University of Mining and Technology(Beijing). 1.. 中国矿业大学（北京），土地复垦与生态重建研究所. Lee Ji-Hyun . September.22. nd. 2010 Beijing, PRC . Contents. Introduction. Policies and legislation . Planning. Practice . Case. Conclusion . Introduction . characteristics of the mining industry in . J. Carmona. R. Gavaldà. UPC (Barcelona, Spain). 1. Outline. The Advent of Process Mining (PM). T. he challenge of Concept Drift (CD). Key ingredients. Online strategy for CD in PM. Experiments. Work in progress. parameters for abdominal forensic CT scans . Pernille . A Nielsen. 1. , Dina M Bech. 1. , Julie B Nielsen. 1. . Pernille L Hansen. 1. , Dennis L Hansen. 2, 3. Svea D . Mørup. 1. , Peter . M Leth. 4. What is process mining?. Process for a pizza delivery service. All process mining techniques assume that it is possible to sequentially record . events. .. Each event refers to an . activity. (i.e., a well-defined step in some process).. Credit: Gaby . Matalon. What is Data Mining?. The. . process . of analyzing data from different perspectives and summarizing it into useful information. It . uncovers patterns . in a large set of data. Bamshad Mobasher. DePaul University. 2. From Data to Wisdom. Data. The raw material of information. Information. Data organized and presented by someone. Knowledge. Information read, heard or seen and understood and integrated.