Providing explanations for the intelligent monitoring of business workflows using case-based reasoning

Abstract

This paper presents an approach for providing explanation to the intelligent diagnosis and monitoring of business workflows based on operation data in the form of temporal log date. The representation of workflow related case knowledge in this research using graphs is explained. Workflow cases are represented in terms of events and their corresponding temporal relationships. The matching and CBR retrieval mechanisms used in this research are explained and the architecture of an integrated intelligent monitoring system is shown. The paper contains an illustration and evaluation of the approach based on experiments on real data from a university quality assurance exam moderation system. It is shown that a graph matching based similarity measure is capable to diagnose problems within business workflows and the results of this reasoning process can be explained to workflow managers and users with the use of graph visualisation techniques.