IMPROVING BUSINESS PROCESS MODELING USING RECOMMENDATION METHOD

Abstract

In modern commerce, the specialization of the business process and frequent changes of custom demands require the capacity of the modeling process for enterprises effectively and efficiently. Existing processes improving business modeling use workflow mining and process retrieval and require much manual work. In this paper workflow recommendation technique is proposed to provide process designers with support for automatically creating the new business process that is under deliberation. With the help of the minimum depth-first search (DFS) codes of business process graphs for calculating the distance between process fragments and select candidate node sets for recommendation purpose. We will implement recommendation method for improving the modeling efficiency and accuracy. And last, based on both synthetic and real-world datasets, we will compare the proposed method with other methods and the experiment results prove its effectiveness for practical applications