Process Model Discovery: A Method Based on Transition System Decomposition

Abstract

Abstract. Process mining aims to discover and analyze processes by extracting information from event logs. Process mining discovery algorithms deal with large data sets to learn automatically process models. As more event data become available there is the desire to learn larger and more complex process models. To tackle problems related to the readability of the resulting model and to ensure tractability, various decomposition methods have been proposed. This paper presents a novel decomposition approach for discovering more readable models from event logs on the basis of a priori knowledge about the event log structure: regular and special cases of the process execution are treated separately. The transition system, corresponding to a given event log, is decomposed into a regular part and a specific part. Then one of the known discovery algorithms is applied to both parts, and finally these models are combined into a single process model. It is proven, that the structural and behavioral properties of submodels are inherited by the unified process model. The proposed discovery algorithm is illustrated using a running example.

Process mining using BPMN: relating event logs and process models

“…In comparison with the approach presented in [17] we plan to build a method on top of the decomposition techniques [1, 23,24] to obtain structural models, preserving behavior recorded in an event log.…”

Model Checking Based Approach for Compliance Checking

“…In the information systems context, this is referred to workflow mining, aiming at retrieving business process models from the analysis of event logs recorded in one or more information systems used to support those processes. Quite a lot of research has been done in this setting ( [12,5,24] to name just a few). The reached results focused on different problems, such as log analysis through clustering, data cleaning from noise, or recognition of particular workflow patterns.…”

Using Event Logs for Local Correction of Process Models

“…Для исправления фрагментов модели, не соответствующих логу, мы применяем методы автоматического синтеза моделей процессов (process discovery). Достаточно большое число таких алгоритмов с разными характеристиками были описаны ранее, а именно [6,7,10,20,[23][24][25]41,42] и другие.…”