Process Discovery using Integer Linear Programming

Werf, Jan Martijn E. M. van der; Dongen, Boudewijn F. van; Hee, K.M. van; Hurkens, Caj Cor; Serebrenik, Alexander

doi:10.3233/fi-2009-136

Cited by 144 publications

(66 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Consider the following set of sequences of executed business process activities: a, c, d, e, f , a, c, b, d, f , a, c, e, d, f and a, e, c, d, f . If we apply ILP-Based process discovery [44], i.e. using region theory, we obtain the process model in Figure 1.…”

Section: Motivationmentioning

confidence: 99%

“…As the example shows there is a clear incentive for process discovery algorithms based on (language-based) region theory. However, the state-of-the-art technique based on language-based region theory [44] has a number of deficiencies. It is not able to guarantee that the resulting Petri net is a workflow net, i.e.…”

Section: Motivationmentioning

confidence: 99%

“…Secondly, we present an effective integrated filtering technique that identifies and ignores infrequent and/or exceptional behaviour. [44], containing a milestone pattern.…”

Section: Motivationmentioning

confidence: 99%

“…In [44] a process discovery algorithm is proposed on top of language-based region theory. The core of the algorithm is an Integer Linear Programming (ILP)-formulation that is solved multiple times using slight variations.…”

Section: Introductionmentioning

confidence: 99%

“…Considering all irregularities together with "normal behaviour" yields incomprehensible models, both in classical region-based synthesis and region-based process discovery techniques. In this paper we tackle these problems by extending and improving existing, region theory based, algorithms [44][45][46]. This paper's contributions are summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Discovering workflow nets using integer linear programming

et al. 2017

View full text Add to dashboard Cite

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 process mining task. State-ofthe-art process discovery algorithms only discover local control flow patterns and are unable to discover complex, non-local patterns. Region theory based techniques, i.e. an established class of process discovery techniques, do allow for discovering such patterns. However, applying region theory directly results in complex, overfitting models, which is less desirable. Moreover, region theory does not cope with guarantees provided by state-of-the-art process discovery algorithms, both w.r.t. structural and behavioural properties of the discovered process models. In this paper we present an ILP-based process discovery approach, based on region theory, that guarantees to discover relaxed sound workflow nets. Moreover, we devise a filtering algorithm, based on the internal working of the ILP-formulation, that is able to cope with the presence of infrequent, exceptional behaviour. We have extensively evaluated the technique using different event logs with different levels of exceptional behaviour. Our experiments show that the presented approach allows us to leverage the inherent shortcomings of existing region-based approaches.

show abstract

Section: Motivationmentioning

confidence: 99%

Section: Motivationmentioning

confidence: 99%

“…Secondly, we present an effective integrated filtering technique that identifies and ignores infrequent and/or exceptional behaviour. [44], containing a milestone pattern.…”

Section: Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations