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P. M. Dixit, H. M. W. Verbeek, J. C. A. M. Buijs, and W. M. P. v. d. Aalst, “Interactive data-driven process model construction,” in 37th international conference on conceptual modeling, er 2018, proceedings, 2018, pp. 251-265.
[Bibtex]@Conference{Dixit18a, Title = {Interactive Data-driven Process Model Construction}, Author = {Dixit, P. M. and Verbeek, H. M. W and Buijs, J. C. A. M. and Aalst, W. M. P. v. d.}, Booktitle = {37th International Conference on Conceptual Modeling, ER 2018, Proceedings}, Year = {2018}, Editor = {Li, Z., and Trujillo, J. C., and Du, X. and Lee, M. L. and Davis, K. C. and Ling, T. W. and Li, G.}, Month = {October}, Pages = {251--265}, Publisher = {Springer}, Series = {LNCS}, Volume = {11157}, Abstract = {Process discovery algorithms address the problem of learning process models from event logs. Typically, in such settings a user's activity is limited to conguring the parameters of the discovery algorithm, and hence the user expertise/domain knowledge can not be incorporated during traditional process discovery. In a setting where the event logs are noisy, incomplete and/or contain uninteresting activities, the process models discovered by discovery algorithms are often inaccurate and/or incomprehensible. Furthermore, many of these automated techniques can produce unsound models and/or cannot discover duplicate activities, silent activities etc. To overcome such shortcomings, we introduce a new concept to interactively discover a process model, by combining a user's domain knowledge with the information from the event log. The discovered models are always sound and can have duplicate activities, silent activities etc. An objective evaluation and a case study shows that the proposed approach can outperform traditional discovery techniques.}, Comment = {Accepted for publication}, Doi = {10.1007/978-3-030-00847-5_19}, Owner = {hverbeek}, Timestamp = {2018.06.18} }