Federated Stochastic Process Discovery Using Grammatical Inference

Abstract

Process discovery studies algorithms for constructing process models that describe control flow of systems that generated given event logs, where an event log is a recording of executed traces of a system, with each trace captured as a sequence of executed actions. Traditional process discovery relies on an event log recorded and stored in a centralized repository. However, in distributed environments, such as cross-organizational process discovery, this centralization raises concerns about data availability, privacy, and high communication and bandwidth demands. To address these challenges, this paper introduces a novel Federated Stochastic Process Discovery (FSPD) approach. FSPD avoids cen..