Call for Papers

Download the call for papers of the special session:

Paper submission guidelines, including paper format and submission system.



2016 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)
December 6-9, 2016, Athens, Greece

The IEEE Task Force on Process Mining is organizing a special session at the 2016 IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2016). The goal of this special session is to allow experts in the area of process mining and data analysis to share new techniques, applications and case studies. Therefore, submissions of papers on new process mining techniques, applications of process mining, business intelligence, process discovery, conformance checking, process intelligence, data analysis, etc. are welcome.

We now live in a time where the amount of data created daily goes easily beyond the storage and processing capabilities of nowadays systems: organizations, governments but also individuals generate large amounts of data at a rate that has started to overwhelm the ability to timely extract useful knowledge from it. Nevertheless, the strategic importance of the knowledge hidden in these data is paramount for effective decision making and need to be extracted quickly in order to effectively react to dynamic situations. Efficient stream processing approaches for real time analysis are crucial for enabling the predictive capabilities required by today’s dynamically and rapidly evolving enterprises.  

Process mining is a relatively young research discipline that sits between computational intelligence and data mining on the one hand and process modeling and analysis on the other hand. The idea of process mining is to discover, monitor and improve real processes (i.e., not assumed processes) by extracting knowledge from event logs readily available in today's systems. Since the work of medium-large enterprises is typically governed by business processes, it is very common to have event data generated as result of such process executions that can be used as input for process mining techniques.


 - Storage and extraction of process logs
 - Process mining approaches
 - Online process mining (stream processing)
 - Distributed approaches for process mining
 - Event log obfuscation
 - Privacy-aware process mining
 - Business process intelligence
 - Data mining for process management
 - Specific computational intelligence applications in   process mining
 - Case studies and empirical evaluations


Paper submission: July 18, 2016 August 15, 2016
Decision: September 12, 2016 September 26, 2016
Final paper submission: October 10, 2016


Andrea Burattin, University of Innsbruck, Austria
Fabrizio M. Maggi, University of Tartu, Estonia
Chiara Di Francescomarino,  FBK, Italy


Visit the session website for detailed submission information.

Andrea Burattin,
Jul 17, 2016, 12:19 AM
Andrea Burattin,
Jul 17, 2016, 12:18 AM