A recursive paradigm for aligning observed behavior of large structured process models

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hdl:2117/99940
Document typeConference report
Defense date2016
PublisherSpringer
Rights accessOpen Access
Abstract
The alignment of observed and modeled behavior is a crucial problem in process mining, since it opens the door for conformance checking and enhancement of process models. The state of the art techniques for the computation of alignments rely on a full exploration of the combination of the model state space and the observed behavior (an event log), which hampers their applicability for large instances. This paper presents a fresh view to the alignment problem: the computation of alignments is casted as the resolution of Integer Linear Programming models, where the user can decide the granularity of the alignment steps. Moreover, a novel recursive strategy is used to split
the problem into small pieces, exponentially reducing the complexity of the ILP models to be solved. The contributions of this paper represent a promising alternative to fight the inherent complexity of computing alignments for large instances.
CitationTaymouri, F., Carmona, J. A recursive paradigm for aligning observed behavior of large structured process models. A: International Conference on Business Process Management. "Business Process Management: 14th International Conference, BPM 2016, Rio de Janeiro, Brazil, September 18-22, 2016: proceedings". Rio de Janeiro: Springer, 2016, p. 197-214.
ISBN978-3-319-45348-4
Publisher versionhttp://link.springer.com/chapter/10.1007/978-3-319-45348-4_12
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