Provided by: Eindhoven University of Technology
Topic: Big Data
Date Added: Jun 2014
Process discovery techniques make it possible to automatically derive process models from event data. However, often one is not only interested in discovering the control-flow but also in answering questions like \"What do the cases that are late have in common?\", \"What characterizes the workers that skip this check activity?\", and \"Do people work faster if they have more work?\", etc. Such questions can be answered by combining process mining with classification (e.g., decision tree analysis). Several authors have proposed ad-hoc solutions for specific questions, e.g., there is work on predicting the remaining processing time and recommending activities to minimize particular risks.