Using metadata for recommending business process

With the increasing development of business process techniques in many enterprises and organizations, business process recommendation has become a dramatic research area of business process management techniques. However, there are some problems in current business process recommendation approaches, which rely on simple metrics such as structural, textual, or behavioral similarity, or which generally rely on specific structures without typical metadata features. To improve the availability of process description and recommendation, an approach for recommending processes is proposed based on metadata. The concept of business process description framework (BPDF) is first constructed based on MFI-5. According to BPDF, similarity feature set (SFS) of the process is defined. The processes are further identified and quantified using SFS, so that the process vectors are obtained. And the similarity measure algorithm is utilized to calculate the similarity between any two vectors, and the similarity matrix of the processes can then be extracted. According to the results of processes similarity measurement, these processes are ranked to provide support for process recommendation. An empirical experiment shows that the proposed approach can be effectively applied to actual scenarios of process recommendation.