Leopold, H., van der Aa, H., Offenberg, J., & Reijers, H. A. (2019). Using Hidden Markov Models for the accurate linguistic analysis of process model activity labels. Information Systems, 83, 30-39. DOI: 10.1016/j.is.2019.02.005 Abstract Many process model analysis techniques rely on the accurate analysis of the natural language contents captured in the models’ activity labels. Read More …
Li, G., & de Carvalho, R. M. (2019). Process mining in social media: applying object-centric behavioral constraint models. IEEE Access, 7, 84360-84373. [8746275]. DOI: 10.1109/ACCESS.2019.2925105 Abstract The pervasive use of social media (e.g., Facebook, Stack Exchange, and Wikipedia) is providing unprecedented amounts of social data. Data mining techniques have been widely used to extract knowledge Read More …
Hassani, M., van Zelst, S. J., & van der Aalst, W. M. P. (2019). On the application of sequential pattern mining primitives to process discovery: overview, outlook and opportunity identification. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(6), [e1315]. DOI: 10.1002/widm.1315 Abstract Sequential pattern mining (SPM) is a well-studied theme in data mining, in Read More …
van Zelst, S. J., Bolt Irondio, A. J., Hassani, M., van Dongen, B. F., & van der Aalst, W. M. P. (2019). Online conformance checking: relating event streams to process models using prefix-alignments. International Journal of Data Science and Analytics, 8(3), 269-284. DOI: 10.1007/s41060-017-0078-6 Abstract Companies often specify the intended behaviour of their business processes Read More …
Leemans, S. J. J., & Fahland, D. (2019). Information-preserving abstractions of event data in process mining. Knowledge and Information Systems. DOI: 10.1007/s10115-019-01376-9 Abstract Process mining aims at obtaining information about processes by analysing their past executions in event logs, event streams, or databases. Discovering a process model from a finite amount of event data thereby Read More …
Tax, N., Alasgarov, E. E., Sidorova, N., Haakma, R., & van der Aalst, W. M. P. (2019). Generating time-based label refinements to discover more precise process models. Journal of Ambient Intelligence and Smart Environments, 11(2), 165-182. DOI: 10.3233/AIS-190519 Abstract Process mining is a research field focused on the analysis of event data with the aim Read More …
Dijkman, R., Gao, J., Syamsiyah, A., van Dongen, B., Grefen, P., & ter Hofstede, A. (2019). Enabling efficient process mining on large data sets: realizing an in-database process mining operator. Distributed and Parallel Databases, 38(1), 227-253. https://doi.org/10.1007/s10619-019-07270-1 Abstract Process mining can be used to analyze business processes based on logs of their execution. These execution Read More …
Hassani, M., Töws, D., Cuzzocrea, A., & Seidl, T. (2019). BFSPMiner: an effective and efficient batch-free algorithm for mining sequential patterns over data streams. International Journal of Data Science and Analytics, 8(3), 223-239. DOI: 10.1007/s41060-017-0084-8 Abstract Supporting sequential pattern mining from data streams is nowadays a relevant problem in the area of data stream mining Read More …
Syamsiyah, A., Dongen, B. F. van, & Dijkman, R. M. (2018). Native directly follows operator. arXiv. Abstract Typical legacy information systems store data in relational databases. Process mining is a research discipline that analyzes this data to obtain insights into processes. Many different process mining techniques can be applied to data. In current techniques, an Read More …
Rekik, Molka, Boukadi, Khouloud, Assy, Nour, Gaaloul, Walid & Ben-Abdallah, Hanene (2018). Optimal deployment of configurable business processes in cloud federations. IEEE Transactions on Network and Service Management, Abstract Configurable processes are increasingly being adopted by enterprises that seek experience sharing and best practice adoption. A configurable process is a customizable model that specifies how Read More …
Kalenkova, Anna, Burattin, Andrea, de Leoni, Massimiliano, van der Aalst, Wil & Sperduti, Alessandro (2019). Discovering high-level BPMN process models from event data. Business Process Management Journal, 25(5), 995-1019. DOI: 10.1108/BPMJ-02-2018-0051 Abstract Purpose: The purpose of this paper is to demonstrate that process mining techniques can help to discover process models from event logs, using Read More …
Beemt, A.A.J. van den, Buijs, J.C.A.M. & Aalst, W.M.P. van der (2018). Analysing structured learning behaviour in Massive Open Online Courses (MOOCs) : An approach based on process mining and clustering. International Review of Research in Open and Distance Learning, 19(5), 38-60. Abstract The increasing use of digital systems to support learning leads to a Read More …
Leemans, S.J.J., Fahland, D. & van der Aalst, W.M.P. (2018). Scalable process discovery and conformance checking. Software and Systems Modeling, 17(2), 599-631. Abstract Considerable amounts of data, including process events, are collected and stored by organisations nowadays. Discovering a process model from such event data and verification of the quality of discovered models are important Read More …
Lee, Wai Lam Jonathan, Verbeek, H.M.W., Munoz-Gama, Jorge, van der Aalst, Wil M.P. & Sepúlveda, Marcos (2018). Recomposing conformance : Closing the circle on decomposed alignment-based conformance checking in process mining. Information Sciences, 466, 55-91. Abstract In the area of process mining, efficient conformance checking is one of the main challenges. Several process mining vendors Read More …
Jalali, A., Maggi, F.M. & Reijers, H.A. (2018). A hybrid approach for aspect-oriented business process modeling. Journal of Software : Evolution and Process, 30(8):e1931 Abstract Separation of concerns has long been an important strategy to deal with complexity when developing a system. Some concerns (like security) are scattered through the whole system, and different modules Read More …
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 …
Tax, N., Sidorova, N. & van der Aalst, W.M.P. (2019). Discovering more precise process models from event logs by filtering out chaotic activities. Journal of Intelligent Information Systems, 52(1), 107-139. DOI: 10.1007/s10844-018-0507-6 Abstract Process Discovery is concerned with the automatic generation of a process model that describes a business process from execution data of that 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 …
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 …
