Computer Science ›› 2016, Vol. 43 ›› Issue (5): 193-197.doi: 10.11896/j.issn.1002-137X.2016.05.035

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Business Process Model Abstraction Based on Cluster Analysis

SUN Shanwu, WANG Nan and OUYANG Dantong   

  • Online:2018-12-01 Published:2018-12-01

Abstract: ion Based on Cluster Analysis SUN Shan-wu1,2 WANG Nan1,2 OUYANG Dan-tong3 (College of Management Science and Information Engineering,Jilin University of Finance and Economics,Changchun 130117,China)1 (Laboratory of Logistics Industry Economy and Intelligent Logistics,Jilin University of Finance and Economics,Changchun 130117,China)2 (Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012,China)3 Abstract A prominent business process model abstraction(BPMA) use case is a construction of a process “quick view” for rapidly comprehending a complex process.Some researchers propose the process abstraction methods to aggregate the activities on the basis of their semantic similarity.Most of these methods focus on k-means cluster analysis which partitions an activity set into k clusters(k is predefined by users) and assigns an activity to a cluster whose centroid is the closest to this activity.But in fact,the number of the abstract activities(clusters or subprocesses) is unknown so that which activities are assigned to the same subprocess tends to depend on the designers’ experiences or modeling habits.Moreover,if the activities are not part of particular cohesive groups from the point of view of experienced mo-delers,the initial merging decisions may contain some errors.In this paper,the virtual document was introduced to represent activities and process models in order to eliminate the constraint of using the particular attributes of activities as the dimensions of vector spaces.And an approach was presented that exploits an industrial process model repository to derive a distance threshold between an activity and the subprocess it belongs to.According to this threshold,an algorithm was proposed to generate a possible number k of the clusters.By using k as a parameter and the distance threshold as a further constraint,a clustering procedure was given to aggregate the activities into different clusters.In an experimental validation,we compared both the proposed approach and k-means clustering(without the distance threshold as a further constraint) with actual model decisions,showing a stronger correlation between the proposed approach and actualmodel decisions.As such,this paper contributes to the development of modeling support for effective process model abstraction,easing the use of business process models in practice.

Key words: Business process model abstraction,Clustering analysis,Virtual document,Activity aggregation

[1] Mendling J,Reijers H A,van der Aalst W M P.Seven Process Modeling Guidelines(7pmg)[J].Information and Software Technology,2010,52(2):127-136
[2] Smirnov S,Dijkman R,Mendling J,et al.Meronymy-based aggregation of activities in business process models[J].Conceptual Modeling-ER 2010,Lecture Notes in Computer Science,2010,6412:1-14
[3] Smirnov S,Reijers H A,Weske M H,et al.Business process model abstraction:a definition,catalog,and survey[J].Distributed and Parallel Databases,2012,30(1):63-99
[4] Smirnov S.Business Process Model Abstraction[D].Germany:University of Potsdam,2012
[5] Polyvyanyy A,Smirnov S,Weske M.Reducing Complexity of Large EPCs[C]∥MobIS.Saarbrücken,Germany,2008 :195-207
[6] Polyvyanyy A,Smirnov S,Weske M.On Application of Structural Decomposition for Process Model Abstraction[C]∥Proceedings of the BPSC 2009.Leipzig,2009:110-122
[7] Vanhatalo J,Vlzer H,Koehler J.The Refined Process Structure Tree[C]∥Proceedings of the 6th International Conference on Business Process Management(BPM 2008).Milan,Italy,2008:100-115
[8] Smirnov S,Reijers H A,Weske M.A Semantic Approach for Business Process Model Abstraction[M]∥Advanced Information Systems Engineering:23rd International Conference(CAiSE 2011).London,UK,June 20-24,2011.Springer,2011:497-511
[9] Weidlich M,Dijkman R,Mendling J.The ICoP framework-Identification of correspondences between process models,Advanced Information Systems Engineering[M]∥Advanced Infromation Systems Engineering:22nd International Conference(CAiSE 2010).Hammamet,Tunisia,June 7-9,2010.Springer,2010:483-498
[10] Reijers H A,Mendling J,Dijkman R M.On the Usefulness of Subprocesses in Business Process Models:BPM Center Report BPM-10-03[R].BPMcenter.org,2010
[11] Qu Y,Hu W,Cheng G.Constructing virtual documents for ontology matching[C]∥Proceedings of the 15th International Conference on World Wide Web.Edinburgh,Scetland,UK,2006:23-31
[12] Porter M F.An algorithm for suffix stripping[J].Program,1980,14(3):130-137
[13] Euzenat J,Shvaiko P.Ontology matching[M].Springer-Verlag,2007
[14] Schae_er S E.Graph Clustering[J].Computer Science Review,2007,1(1):27-64
[15] Zhou S,Xu Z,Tang X.New method for determining optimalnumber of clusters in K-means clustering algorithm [J].Computer Engineering and Applications,2010,46(16):27-31
[16] Franzblau A N.A Primer of Statistics for Non-statisticians[M]∥Harcourt,Brace & World New York.1958
[17] Liu D,Shen M.Workflow Modeling for Virtual Processes:anOrder-preserving Process-view Approach[J].Information Systems,2003,28(6):505-532

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