Decomposed process mining with DivideAndConquer

Abstract

Many known process mining techniques scale badly in the number of activities in an event log. Examples of such techniques include the ILP Miner and the standard replay, which also uses ILP techniques. To alleviate the problems these techniques face, we can decompose a large problem (with many activities) into a number of small problems (with few activities). Expectation is, that the run times of such a decomposed setting will be faster than the run time of the original setting. This paper presents the DivideAndConquer tool, which allows the user to decompose a large problem into small problems, to run the desired discovery or replay technique on each of these decomposed problems, and to merge the results into a single result, which can then be shown to the user