Matching Business Process Models Using Positional Passage-Based Language Models

Business operations are often documented by business process models. Use cases such as system validation and process harmonization require the identification of correspondences between activities, which is supported by matching techniques that cope with textual heterogeneity and differences in model granularity. In this paper, we present a matching technique that is tailored towards models featuring textual descriptions of activities. We exploit these descriptions using ideas from language modelling. Experiments with real-world process models reveal that our technique increases recall by up to factor five, largely without compromising precision, compared to existing approaches.

[1]  ChengXiang Zhai,et al.  Positional language models for information retrieval , 2009, SIGIR.

[2]  Krzysztof Czarnecki,et al.  Matching business process workflows across abstraction levels , 2012, MODELS'12.

[3]  Remco M. Dijkman,et al.  Aligning Business Process Models , 2009, 2009 IEEE International Enterprise Distributed Object Computing Conference.

[4]  Mathias Weske,et al.  Behavioral Similarity - A Proper Metric , 2011, BPM.

[5]  Zohra Bellahsene,et al.  Matching and Alignment: What Is the Cost of User Post-Match Effort? - (Short Paper) , 2011, OTM Conferences.

[6]  Jianhua Lin,et al.  Divergence measures based on the Shannon entropy , 1991, IEEE Trans. Inf. Theory.

[7]  W. Bruce Croft,et al.  A general language model for information retrieval , 1999, CIKM '99.

[8]  Mark Levene,et al.  Search Engines: Information Retrieval in Practice , 2011, Comput. J..

[9]  W. Bruce Croft,et al.  Passage retrieval based on language models , 2002, CIKM '02.

[10]  Tharam S. Dillon,et al.  On the Move to Meaningful Internet Systems, OTM 2010 , 2010, Lecture Notes in Computer Science.

[11]  Avigdor Gal,et al.  Tuning the ensemble selection process of schema matchers , 2010, Inf. Syst..

[12]  Erhard Rahm,et al.  Schema Matching and Mapping , 2013, Schema Matching and Mapping.

[13]  Remco M. Dijkman,et al.  Probabilistic Optimization of Semantic Process Model Matching , 2012, BPM.

[14]  Jana Koehler,et al.  The refined process structure tree , 2008, Data Knowl. Eng..

[15]  Mathias Weske,et al.  A Foundational Approach for Managing Process Variability , 2011, CAiSE.

[16]  Remco M. Dijkman,et al.  The ICoP Framework: Identification of Correspondences between Process Models , 2010, CAiSE.

[17]  Kevin Lano,et al.  Slicing of UML models using model transformations , 2010, MODELS'10.