On comparing manual and automatic generated textual descriptions of business process models

AbstractSeveral organizations maintain textual process descriptions alongside graphical process descriptions to make them usable for all stakeholders. Maintaining textual process descriptions in the presence of continuously changing processes is a labor‐intensive task. Therefore, the automatic generation of textual descriptions is desirable. However, the trade‐offs between the manual and automatic generation of descriptions are yet to be investigated. To that end, this paper aims to answer two vital questions. How similar are the descriptions generated by the two approaches? What is the impact of using the two types of descriptions on process matching? To answer these specific questions, we have generated textual descriptions of 552 process models using the two approaches. To answer the first question, we have applied six text‐matching techniques and established that the descriptions overlap significantly; however, the formulation of sentences is substantially different. For answering the second question, we have used 11 text‐matching techniques to evaluate the impact of both descriptions on process matching. Results show (a) the choice of matching technique, and the type of description, have an impact on the matching performance and (b) vector space model (VSM) is the most appropriate matching technique whereas 5 gram is the worst performing technique.