Process mining is an emerging discipline incorporating methods and tools for the analysis of
system/process executions captured in the form of event logs [1]. Traditionally process …

Existing techniques for automated discovery of process models from event logs generally
produce flat process models. Thus, they fail to exploit the notion of subprocess as well as …

A process model discovered from an event log of a multi-agent system often does not fully
cover certain viewpoints of its architecture. We consider those concerned with the structure …

Abstract Business Process Model and Notation (BPMN) is a de-facto standard for
practitioners working in the Business Process Management (BPM) field. The BPMN standard …

Existing techniques for automated discovery of process models from event logs generally
produce flat process models. Thus, they fail to exploit the notion of subprocess, as well as …

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 mining is a relatively new field of computer science, which deals with process
discovery and analysis based on event logs. In this paper we consider the problem of …

Process mining techniques use event data from operational and software processes to
discover process models, to check the conformance of predefined process models, and to …

This paper presents a novel extension to the process tree model to support cancelation
behavior, and proposes a novel process discovery technique to discover sound, fitting …

Remaining time prediction of business processes plays an important role in resource
scheduling and plan making. The structural features of single process instance and the …