An Effective Algorithm for Business Process Mining Based on Modified FP-Tree Algorithm

Abstract

A number of business organizations are beginning to realize the importance of business process management. However, process can often go the way they were initially not designed for or a non-efficient performance process model could be designed. To solve this problem, business process mining which can be used as the basis for the business process re-engineering has been recognized to an important concept. However, current research in the domain of process mining has only focused on extracting a workflow-based process model from completed process logs. Thus, there is a limitation in expressing various types of business processes, and moreover, process discovery and log scanning take a considerable amount of time. In this paper, we present a modified FP-tree algorithm for FP-tree based business processes, which are used for association analysis in data mining. Our modified algorithm supports the discovery of an appropriate level of the process model according to the user's need without re-scanning all the process logs during updating.