Лабораторная ФКН: Learning High-Level Process Models from Event Data. Anna Kalenkova, PAIS Lab
November 14, 2017
18.10 – 19.30
Kochnovskii proezd, 3, room 205
Learning High-Level Process Models from Event Data
Научно-учебная лаборатория процессно-ориентированных информационных систем (ПОИС): Старший научный сотрудник
Information systems in different domains, such as healthcare, tourism, banking, government and others, record operational behavior in the form of event logs. The process mining discipline offers dozens of techniques to discover, analyze, and visualize processes running in information systems, based on their event logs. The representational bias (the language for processes representation) plays an important role in the process discovery. In this work, BPMN (Business Process Model and Notation) language was chosen as a representational bias and as a starting point for the process discovery, analysis, and enhancement. BPMN is a common process modeling language, widely used by consultants, managers, analysts, and software engineers in various application domains. This work aims to bridge the gap between process mining techniques and BPMN. Existing techniques are often limited to a single perspective, e.g., just the control flow, subprocesses, or just resources. The goal of this work is to fully support the BPMN specification in the context of process mining and suggest a unified integrated approach allowing for the discovery, analysis and enhancement of hierarchical high-level BPMN models. Such an approach gives an ability to analyze discovered processes in BPMN-compliant tools and even automate their executions, using one of the existing BPMN engines.
Registration is open: computerscience@hse.ru