A Recommendation System to Facilitate Business Process Modeling

Document Type

Article

Publication Date

6-1-2017

Abstract

This paper presents a system that utilizes process recommendation technology to help design new business processes from scratch in an efficient and accurate way. The proposed system consists of two phases: 1) offline mining and 2) online recommendation. At the first phase, it mines relations among activity nodes from existing processes in repository, and then stores the extracted relations as patterns in a database. At the second phase, it compares the new process under construction with the premined patterns, and recommends proper activity nodes of the most matching patterns to help build a new process. Specifically, there are three different online recommendation strategies in this system. Experiments on both real and synthetic datasets are conducted to compare the proposed approaches with the other state-of-the-art ones, and the results show that the proposed approaches outperform them in terms of accuracy and efficiency.

Identifier

84963636480 (Scopus)

Publication Title

IEEE Transactions on Cybernetics

External Full Text Location

https://doi.org/10.1109/TCYB.2016.2545688

ISSN

21682267

PubMed ID

27076482

First Page

1380

Last Page

1394

Issue

6

Volume

47

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