SOLID-M: An ontology-aware quality framework for conceptual models discovered from event data

Abstract

In Process Mining (PM), “high-level” conceptual models of business processes, in the form of directly-follows graphs, Petri nets, and finite-state automata, are discovered from “low-level” event data recorded by information systems. The quality of the discovered models is usually assessed by measures that depend on assumptions made by discovery algorithms; for example, they often assume that sequences of activities recorded in the event data do not interfere. Models produced by recent discovery algorithms consider domain knowledge and relax these assumptions, making traditional PM measures less suitable for evaluating their quality. This paper proposes an ontology-aware framework, called SOL..