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{"title":"Object-Centric Process Mining Using Process Cubes","authors":"Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst","volume":167,"journal":"International Journal of Mechanical and Industrial Engineering","pagesStart":538,"pagesEnd":546,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10011600","abstract":"Process mining provides ways to analyze business<br \/>\r\nprocesses. Common process mining techniques consider the process<br \/>\r\nas a whole. However, in real-life business processes, different<br \/>\r\nbehaviors exist that make the overall process too complex to interpret.<br \/>\r\nProcess comparison is a branch of process mining that isolates<br \/>\r\ndifferent behaviors of the process from each other by using process<br \/>\r\ncubes. Process cubes organize event data using different dimensions.<br \/>\r\nEach cell contains a set of events that can be used as an input to apply<br \/>\r\nprocess mining techniques. Existing work on process cubes assume<br \/>\r\nsingle case notions. However, in real processes, several case notions<br \/>\r\n(e.g., order, item, package, etc.) are intertwined. Object-centric<br \/>\r\nprocess mining is a new branch of process mining addressing multiple<br \/>\r\ncase notions in a process. To make a bridge between object-centric<br \/>\r\nprocess mining and process comparison, we propose a process cube<br \/>\r\nframework, which supports process cube operations such as slice and<br \/>\r\ndice on object-centric event logs. To facilitate the comparison, the<br \/>\r\nframework is integrated with several object-centric process discovery<br \/>\r\napproaches.","references":"[1] A. Bolt and W. van der Aalst, \u201cMultidimensional process mining using\r\nprocess cubes,\u201d in Enterprise, Business-Process and Information Systems\r\nModeling. Springer, 2015, pp. 102\u2013116.\r\n[2] J. Ribeiro and A. Weijters, \u201cEvent cube: another perspective on business\r\nprocesses,\u201d in International Conferences On the Move to Meaningful\r\nInternet Systems. Springer, 2011, pp. 274\u2013283.\r\n[3] C. Chen, X. Yan, F. Zhu, J. Han, and S. Y. Philip, \u201cGraph OLAP: a\r\nmulti-dimensional framework for graph data analysis,\u201d Knowledge and\r\ninformation systems, vol. 21, no. 1, pp. 41\u201363, 2009.\r\n[4] W. van der Aalst, \u201cObject-centric process mining: Dealing with\r\ndivergence and convergence in event data,\u201d in International Conference\r\non Software Engineering and Formal Methods. Springer, 2019, pp.\r\n3\u201325.\r\n[5] T. Vogelgesang and H.-J. Appelrath, \u201cMultidimensional process mining:\r\na flexible analysis approach for health services research,\u201d in Proceedings\r\nof the Joint EDBT\/ICDT 2013 Workshops, 2013, pp. 17\u201322.\r\n[6] W. van der Aalst, \u201cProcess cubes: Slicing, dicing, rolling up and drilling\r\ndown event data for process mining,\u201d in Asia-Pacific Conference on\r\nBusiness Process Management. Springer, 2013, pp. 1\u201322.\r\n[7] R. Andreswari and M. A. Rasyidi, \u201cOLAP cube processing of production\r\nplanning real-life event log: A case study,\u201d in ICoIESE 2018. Atlantis\r\nPress, 2019.\r\n[8] M. R. H. Nik, W. van der Aalst, and M. F. Sani, \u201cBipm: Combining bi\r\nand process mining.\u201d in DATA, 2019, pp. 123\u2013128.\r\n[9] D. Cohn and R. Hull, \u201cBusiness artifacts: A data-centric approach to\r\nmodeling business operations and processes.\u201d IEEE Data Eng. Bull.,\r\nvol. 32, no. 3, pp. 3\u20139, 2009.\r\n[10] K. Bhattacharya, C. Gerede, R. Hull, R. Liu, and J. Su, \u201cTowards formal\r\nanalysis of artifact-centric business process models,\u201d in International\r\nConference on Business Process Management. Springer, 2007, pp.\r\n288\u2013304.\r\n[11] X. Lu, M. Nagelkerke, D. van de Wiel, and D. Fahland, \u201cDiscovering\r\ninteracting artifacts from ERP systems (extended version),\u201d BPM\r\nreports, vol. 1508, 2015.\r\n[12] G. Li, R. M. de Carvalho, and W. van der Aalst, \u201cAutomatic discovery of\r\nobject-centric behavioral constraint models,\u201d in International Conference\r\non Business Information Systems. Springer, 2017, pp. 43\u201358.\r\n[13] A. Berti and W. van der Aalst, \u201cExtracting multiple viewpoint models\r\nfrom relational databases,\u201d in Data-Driven Process Discovery and\r\nAnalysis. Springer, 2018, pp. 24\u201351.\r\n[14] W. van der Aalst and A. Berti, \u201cDiscovering Object-centric Petri nets,\u201d\r\nin Fundamenta Informaticae, 2020.\r\n[15] M. Gupta and A. Sureka, \u201cProcess cube for software defect resolution,\u201d\r\nin Asia-Pacific Software Engineering Conference, vol. 1. IEEE, 2014,\r\npp. 239\u2013246.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 167, 2020"}