Process Discovery from Model and Text Artefacts

Modeling is an important and time consuming part of the business process management life-cycle. An analyst reviews existing documentation and queries relevant domain experts to construct both mental and concrete models of the domain. To aid this exercise, we propose the Rapid Business Process Discovery (R-BPD) framework and prototype tool that can query heterogeneous information resources (e.g. corporate documentation, web-content, code e.t.c.) and rapidly constructproto-models to be incrementally adjusted to correctness by an analyst. This constitutes a departure from building and constructing models toward just editing them. We believe this rapid mixed-initiative modeling will increase analyst productivity by significant orders of magnitude over traditional approaches. Furthermore, the possibility of using the approach in distributed and real-time settings seems appealing and may help in significantly improving the quality of the models being developed w.r.t. being consistent, complete, and concise.

[1]  John H. Boose,et al.  Knowledge Acquisition Tools, Methods, and Mediating Representations , 1990 .

[2]  Wil M. P. van der Aalst,et al.  Workflow Mining: Current Status and Future Directions , 2003, OTM.

[3]  Shazia Wasim Sadiq,et al.  Managing Process Variants as an Information Resource , 2006, Business Process Management.

[4]  Steve M. Easterbrook,et al.  Using ViewPoints for inconsistency management , 1996, Softw. Eng. J..

[5]  Ian Sommerville,et al.  Managing Process Inconsistency Using Viewpoints , 1999, IEEE Trans. Software Eng..

[6]  Jacques Wainer,et al.  Beyond Workflow Mining , 2006, Business Process Management.

[7]  Mathias Weske,et al.  Business Process Management: A Survey , 2003, Business Process Management.

[8]  Barry Shore Bias in the development and use of an expert system: implications for life cycle costs , 1996 .

[9]  Richard C. Waters,et al.  The Requirements Apprentice: Automated Assistance for Requirements Acquisition , 1991, IEEE Trans. Software Eng..

[10]  Thomas R. Gruber,et al.  Automated knowledge acquisition for strategic knowledge , 1989, Machine Learning.

[11]  N. Shadbolt,et al.  Eliciting Knowledge from Experts: A Methodological Analysis , 1995 .

[12]  Wil M. P. van der Aalst,et al.  Decision Mining in ProM , 2006, Business Process Management.

[13]  Gerhard Cronje,et al.  Introduction to Business Management , 1998 .

[14]  Stephen A. White,et al.  Business Process Modeling Notation (BPMN), Version 1.0 , 2004 .

[15]  Eric S. K. Yu,et al.  Models for supporting the redesign of organizational work , 1995, COCS '95.

[16]  Ewan Klein Computational Semantics in the Natural Language Toolkit , 2006, ALTA.

[17]  Aneesh Krishna,et al.  Combined Approach for Supporting the Business Process Model Lifecycle , 2006, PACIS.

[18]  Bashar Nuseibeh,et al.  Coordinating distributed ViewPoints: the Anatomy of a Consistency Check , 1994 .

[19]  Krzysztof Czarnecki,et al.  Classification of Model Transformation Approaches , 2003 .

[20]  Ian Sommerville,et al.  Viewpoints: principles, problems and a practical approach to requirements engineering , 1997, Ann. Softw. Eng..

[21]  Howard Smith,et al.  Business Process Management: The Third Wave , 2003 .

[22]  Wil M. P. van der Aalst,et al.  Mining Social Networks: Uncovering Interaction Patterns in Business Processes , 2004, Business Process Management.

[23]  Achim G. Hoffmann,et al.  Efficient Knowledge Acquisition for Extracting Temporal Relations , 2005, ALTA.

[24]  Cheng Wu,et al.  A three-layered method for business processes discovery and its application in manufacturing industry , 2007, Comput. Ind..