Efficient querying of large process model repositories

Jin, Tao, Wang, Jianmin, La Rosa, Marcello, ter Hofstedee, Arthur, & Wenb, Lijie (2012) Efficient querying of large process model repositories. Computers in Industry, 64(1), pp. 41-49.

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Abstract

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

Impact and interest:

10 citations in Scopus
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11 citations in Web of Science®

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ID Code: 58996
Item Type: Journal Article
Refereed: Yes
Keywords: Business process model, Efficient query, Subgraph isomorphism, Process repository
DOI: 10.1016/j.compind.2012.09.008
ISSN: 0166-3615
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Coyright 2012 Elsevier B.V. All rights reserved.
Deposited On: 09 Apr 2013 22:26
Last Modified: 06 Sep 2016 00:42

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