Process discovery is the task of generating models from event logs. Mining processes that operate in an environment of high variability is an ongoing research challenge because various algorithms tend to produce spaghetti-like models. This is particularly the case when procedural models are generated. A promising direction to tackle this challenge is the usage of declarative process modelling languages like Declare, which summarise complex behaviour in a compact set of behavioural constraints. However, Declare constraints with branching are expensive to be calculated.In addition, it is often the case that hundreds of branching Declare constraints are valid for the same log, thus making, again, the discovery results unreadable. In this paper, we address these problems from a theoretical angle. More specifically, we define the class of Target- Branched Declare constraints and investigate the formal properties it exhibits. Furthermore, we present a technique for the efficient discovery of compact Target-Branched Declare models. We discuss the merits of our work through an evaluation based on a prototypical implementation using both artificial and real-world event logs.

Discovering Target-Branched Declare Constraints / DI CICCIO, Claudio; Maggi, FABRIZIO MARIA; Mendling, Jan. - 8659:(2014), pp. 34-50. (Intervento presentato al convegno 12th International Conference on Business Process Management, BPM 2014 tenutosi a Haifa; Israel) [10.1007/978-3-319-10172-9_3].

Discovering Target-Branched Declare Constraints

Claudio Di Ciccio
;
Fabrizio Maria Maggi;
2014

Abstract

Process discovery is the task of generating models from event logs. Mining processes that operate in an environment of high variability is an ongoing research challenge because various algorithms tend to produce spaghetti-like models. This is particularly the case when procedural models are generated. A promising direction to tackle this challenge is the usage of declarative process modelling languages like Declare, which summarise complex behaviour in a compact set of behavioural constraints. However, Declare constraints with branching are expensive to be calculated.In addition, it is often the case that hundreds of branching Declare constraints are valid for the same log, thus making, again, the discovery results unreadable. In this paper, we address these problems from a theoretical angle. More specifically, we define the class of Target- Branched Declare constraints and investigate the formal properties it exhibits. Furthermore, we present a technique for the efficient discovery of compact Target-Branched Declare models. We discuss the merits of our work through an evaluation based on a prototypical implementation using both artificial and real-world event logs.
2014
12th International Conference on Business Process Management, BPM 2014
Process mining; discovery; declarative processes
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Discovering Target-Branched Declare Constraints / DI CICCIO, Claudio; Maggi, FABRIZIO MARIA; Mendling, Jan. - 8659:(2014), pp. 34-50. (Intervento presentato al convegno 12th International Conference on Business Process Management, BPM 2014 tenutosi a Haifa; Israel) [10.1007/978-3-319-10172-9_3].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1372929
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