Aligning modeled and observed behavior: A compromise between computation complexity and quality
Visualitza/Obre
10.1007/978-3-319-59536-8_7
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/127950
Tipus de documentText en actes de congrés
Data publicació2017
EditorSpringer
Condicions d'accésAccés obert
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Abstract
Certifying that a process model is aligned with the real process executions is perhaps the most desired feature a process model may have: aligned process models are crucial for organizations, since strategic decisions can be made easier on models instead of on plain data. In spite of its importance, the current algorithmic support for computing alignments is limited: either techniques that explicitly explore the model behavior (which may be worst-case exponential with respect to the model size), or heuristic approaches that cannot guarantee a solution, are the only alternatives. In this paper we propose a solution that sits right in the middle in the complexity spectrum of alignment techniques; it can always guarantee a solution, whose quality depends on the exploration depth used and local decisions taken at each step. We use linear algebraic techniques in combination with an iterative search which focuses on progressing towards a solution. The experiments show a clear reduction in the time required for reaching a solution, without sacrificing significantly the quality of the alignment obtained.
CitacióDongen, B. [et al.]. Aligning modeled and observed behavior: A compromise between computation complexity and quality. A: International Conference on Advanced Information Systems Engineering. "Advanced Information Systems Engineering, 29th International Conference, CAiSE 2017: Essen, Germany, June 12-16, 2017: proceedings". Berlín: Springer, 2017, p. 94-109.
ISBN978-3-319-59536-8
Versió de l'editorhttps://link.springer.com/chapter/10.1007/978-3-319-59536-8_7
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