Mining task post-conditions: Automating the acquisition of process semantics

Authors

Metta Santiputri, University of WollongongFollow
Aditya K. Ghose, University of WollongongFollow
Hoa K. Dam, University of WollongongFollow

RIS ID

113944

Publication Details

Santiputri, M., Ghose, A. & Dam, H. (2017). Mining task post-conditions: Automating the acquisition of process semantics. Data and Knowledge Engineering,109 112-125.

Abstract

2017 Elsevier B.V.Semantic annotation of business process model in the business process designs has been addressed in a large and growing body of work, but these annotations can be difficult and expensive to acquire. This paper presents a data-driven approach to mining and validating these annotations (and specifically context-independent semantic annotations). We leverage event objects in process execution histories which describe both activity execution events (typically represented as process events) and state update events (represented as object state transition events). We present an empirical evaluation, which suggests that the approach provides generally reliable results.