Nour Assy est de passage dans le département pour quelques jours. Elle se propose de nous faire une présentation de ses travaux le vendredi 19 mai à 11h30 en C06.

Title: Discovering Hierarchical Consolidated Models from Process Families

Abstract: As event data are becoming omnipresent, the importance of process mining is becoming more and more significant. Process mining allows to automatically discover, analyse and improve business processes from execution data referred to as “event logs”. Traditionally, event logs are assumed to describe the execution of static and homogeneous processes. However, business requirements and regulations are continuously changing, and so are the processes. Municipalities, banks, telecommunication service providers and many others execute the same processes but with personalized features. This results in a family of related event logs that can be mined to discover their underlying process variants. Discovering a collection of disconnected variants creates redundancy and turns the management and maintenance of the process family a difficult task. Instead, organizations need to efficiently analyze and track changes in their processes in a unified way. In this talk, we start by providing some pointers to process mining literature and current challenges of mining process families. Then we present an approach for discovering hierarchical models from collections of event logs. The discovered hierarchy consists of nested process fragments and allows to efficiently explore the commonalities and differences among the variants in a process family.

Biography: Nour Assy is a Postdoc in the Architecture of Information Systems group at the Technische Universiteit Eindhoven, the Netherlands. Nour obtained her PhD degree in Computer science from Telecom SudParis in 2015 and her MSc degree from Lebanese University, Lebanon. Her research interests are in (Software) process mining, process variability management and cloud computing.