van Zelst, S.J., van Dongen, B.F. & van der Aalst, W.M.P. (2018). Event stream-based process discovery using abstract representations. Knowledge and Information Systems, 54(2), 407-435. Abstract The aim of process discovery, originating from the area of process mining, is to discover a process model based on business process execution data. A majority of process discovery Read More …
van Zelst, S.J., van Dongen, B.F., van der Aalst, W.M.P. && Verbeek, H.M.W. (2018). Discovering workflow nets using integer linear programming. Computing, 100(5), 529-556. Abstract Process mining is concerned with the analysis, understanding and improvement of business processes. Process discovery, i.e. discovering a process model based on an event log, is considered the most challenging Read More …
Tax, Niek, Dalmas, Benjamin, Sidorova, Natalia, van der Aalst, Wil M.P. & Norre, Sylvie (2018). Interest-driven discovery of local process models. Information Systems, 77, 105-117. Abstract Local Process Models (LPM) describe structured fragments of process behavior occurring in the context of less structured business processes. Traditional LPM discovery aims to generate a collection of process Read More …
Tax, N., Lu, X., Sidorova, N., Fahland, D. & van der Aalst, W.M.P. (2018). The imprecisions of precision measures in process mining. Information Processing Letters, 135, 1-8. Abstract In process mining, precision measures are used to quantify how much a process model overapproximates the behavior seen in an event log. Although several measures have been Read More …
Polato, Mirko, Sperduti, Alessandro, Burattin, Andrea & de Leoni, Massimiliano (2018). Time and activity sequence prediction of business process instances. Computing, 100(9), 1005-1031 Abstract The ability to know in advance the trend of running process instances, with respect to different features, such as the expected completion time, would allow business managers to timely counteract to Read More …
Mendling, J., Weber, I., van der Aalst, W.M.P., vom Brocke, J., Cabanillas, C., Daniel, F., Debois, S., Di Ciccio, C., Dumas, M., Dustdar, S., Gal, A., García-Bañuelos, L., Governatori, G., Hull, R., La Rosa, Marcello, Leopold, Henrik, Leymann, Frank, Recker, Jan, Reichert, Manfred, Reijers, H.A., Rinderlema, Stefanie, Solti, Andreas, Rosemann, Michael, Schulte, Stefan, Singh, Munindar Read More …
Mannhardt, F., de Leoni, M., Reijers, H.A., van der Aalst, W.M.P. & Toussaint, P. (2018). Guided Process Discovery : A Pattern-based Approach. Information Systems, 76, 1-18 Abstract Process mining techniques analyze processes based on events stored in event logs. Yet, low-level events recorded by information systems may not directly match high-level activities that make sense Read More …
Fahland, Dirk & Völzer, Hagen (2018). Dynamic skipping and blocking, dead path elimination for cyclic workflows, and a local semantics for inclusive gateways. Information Systems, 78, 126-143. Abstract We propose and study dynamic versions of the classical flexibility constructs ‘skip’ and ‘block’ for workflows and motivate and define a formal semantics for them. We show Read More …
Bolt, A., de Leoni, M. & van der Aalst, W.M.P. (2018). Process variant comparison: using event logs to detect differences in behavior and business rules. Information Systems, 74(1), 53-66. Abstract This paper addresses the problem of comparing different variants of the same process. We aim to detect relevant differences between processes based on what was Read More …
Alizadeh, M., Lu, X., Fahland, D., Zannone, N. & van der Aalst, W.M.P. (2018). Linking data and process perspectives for conformance analysis. Computers and Security, 73, 172-193. Abstract The detection of data breaches has become a major challenge for most organizations. The problem lies in the fact that organizations often lack proper mechanisms to control Read More …
van der Aalst, Wil (2018). Spreadsheets for business process management : Using process mining to deal with “events” rather than “numbers”?. Business Process Management Journal, 24(1), 105-127. Abstract Purpose: Process mining provides a generic collection of techniques to turn event data into valuable insights, improvement ideas, predictions, and recommendations. This paper uses spreadsheets as a Read More …
This course focuses on enterprise information systems that are driven by models, i.e., instead of constructing code these systems are assembled, configured or generated using a model-driven approach. Of particular interest are so-called “process-aware” information systems. Typical examples are workflow management systems and the process engines of ERP, CRM, PDM and other enterprise information systems. Read More …
Organizations are constantly trying to improve the way their businesses perform. To this end, managers have to take decisions on changes to the operational processes. However, these changes are never without consequences and often high costs are involved. Therefore, it is of the utmost importance that these decisions are supported by a thorough analysis of Read More …
van der Aa, H., Leopold, H. & Reijers, H.A. (2018). Checking process compliance against natural language specifications using behavioral spaces. Information Systems, 78, 83-95 Abstract Textual process descriptions are widely used in organizations since they can be created and understood by virtually everyone. Because of their widespread use, they also provide a valuable source for Read More …
