Filtering and Sampling Object-Centric Event Logs

arXiv (Cornell University)

Abstract

The scalability of process mining techniques is one of the main challenges to tackling the massive amount of event data produced every day in enterprise information systems. To this purpose, filtering and sampling techniques are proposed to keep a subset of the behavior of the original log and make the application of process mining techniques feasible. While techniques for filtering/sampling traditional event logs have been already proposed, filtering/sampling object-centric event logs is more challenging as the number of factors (events, objects, object types) to consider is significantly higher. This paper provides some techniques to filter/sample object-centric event logs.

Authors 1

1. Alessandro Berti corresponding Aachen Process and Data Science Group

   RWTH Aachen University · Fraunhofer Institute for Applied Information Technology

   Affiliation as printed

   Fraunhofer Institute of Technology (FIT) , Sankt Augustin , Germany

   Process and Data Science Group @ RWTH Aachen , Aachen , Germany