Methods and techniques for discovering taxonomies of behavioral process models

Modeling behavioral aspects of business processes is a hard and costly task, which usually requires heavy intervention of business experts. This explains the increasing attention given to process mining techniques, which automatically extract behavioral process models from log data. In the case of complex processes, however, the models identified by classical process mining techniques are hardly useful to analyze business operations at a suitable abstraction level. In fact, the need of process abstraction emerged in several application scenarios, and abstraction methods are already supported in some business-management platforms, which allow users to manually define abstract views for the process at hand. Therefore, it comes with no surprise that process mining research recently considered the issue of mining processes at different abstraction levels, mainly in the form of a taxonomy of process models, as to overcome the drawbacks of traditional approaches. This paper presents a general framework for the discovery of such a taxonomy, and offers a survey of different kinds of basic techniques that can be exploited to this purpose: (1) workflow modeling and discovery techniques, (2) clustering techniques enabling the discovery of different behavioral process classes, and (3) activity abstraction techniques for associating a generalized process model with each higher level taxonomy node.