Tenth International Workshop on Business Process Intelligence (BPI’14) to be held in conjunction with BPM’14

The BPI 2014 workshop will be held on 8 September 2014, from 9:00h to 17:00h. The accepted papers will be presented during the workshop and authors have 20 minutes for their presentations and 10 minutes for discussion.

At the end of the workshop, the winner for the third international Business Process Intelligence Challenge (BPI Challenge) will be announced.

Program

Business Process Intelligence is an area that spans process discovery, conformance checking, process mining, predictive analytics and many other techniques that are all gaining interest and importance in industry and research. BPI refers to the application of various measurement and analysis techniques in the area of business process management. In practice, BPI is embodied in tools for managing process execution quality by offering several features such as analysis, prediction, monitoring, control, and optimization.

The goal of this workshop is to provide a better understanding and a more appropriate support of company processes at design time and the way they are handled at runtime, focussing on processes in isolation as well as the interplay between many parallel processes both within and between companies.

We aim to bring together practitioners and researchers from different communities such as business process management, information systems research, business administration, software engineering, artificial intelligence, process mining, and data mining who share an interest in the analysis of business processes and process-aware information systems. The workshop aims at discussing the current state of ongoing research and sharing practical experiences.

The list of topics that are relevant to the BPI workshop includes the following, but is not limited to:

Analysis Techniques at design time and/or runtime:

• Mining of business processes from event logs
• Mining of non process aware systems / event streams
• Multi perspective process mining
• Statistical analysis in the business process management lifecycle
• Predictive analytics
• Recommender systems
• Conformance / compliance analysis
• Root cause analysis for process deviations
• Business process visualization
• Visualization of process mining results
• Machine-learning and business processes
• Measurement of business process models and business process modeling
• Information retrieval related to business process management
• Similarity related to processes and cases
• Integration of processes and process models
• Mathematical optimization of business processes
• Simulation of business processes

Applications of such analysis techniques and case studies in:

• Performance Measurement of business processes
• Business Process Reengineering
• Business Process Quality
• Emergent workflows
• Process discovery
• Conformance and risk management for business processes
• Operations Management and Six Sigma
• Data warehousing
• Static and dynamic optimization
• Self-management
• Monitoring of business processes
• Resource Allocation in business processes
• Prediction
• Dynamic composition of business processes

Submitted papers will be evaluated on the basis of significance, originality and technical quality. The length of a paper must not exceed 12 pages, and there is no possibility to buy additional pages. Authors are requested to prepare submissions according to the LNCS/LNBIP format specified by Springer. The title page must contain a short abstract and a classification of the topics covered, preferably using the list of topics above. Papers should be submitted electronically through easychair. Members of an international and solid program committee will review all submissions. Each paper will be reviewed by 3 PC members guaranteeing that only papers presenting high quality and innovative research and practice issues in areas relevant to the workshop theme will be accepted.

The workshop is co-organized by the IEEE Task Force on Process Mining. The goal of this Task Force is to promote the research, development, education and understanding of process mining. For more information about the activities of the IEEE Task Force on Process Mining and its members see https://www.win.tue.nl/ieeetfpm/

• Wil van der Aalst, Eindhoven University of Technology, The Netherlands
• Ana Karla Alves de Medeiros, Centraal Beheer Achmea, The Netherlands
• Boualem Benatallah, University of New South Wales, Australia
• Walid Gaaloul, Insitut Telecom, France
• Gianluigi Greco, University of Calabria, Italy
• Daniela Grigori, University of Versailles St-Quentin an Yvelines, France
• Antonella Guzzo, University of Calabria, Italy
• Michael Leyer, Frankfurt School of Finance & Management, Germany
• Jan Mendling, Wirtschaftsuniversität Wien, Austria
• Oscar Pastor, University of Valencia, Spain
• Viara Popova, Tallinn University of Technology, Tallinn
• Manfred Reichert, University of Twente, The Netherlands
• Michael Rosemann, Queensland University of Technology, Australia
• Anne Rozinat, Fluxicon, The Netherlands
• Domenico Sacca, Università degli studi della Calabri, Italy
• Phina Soffer, University of Haita, Israel
• Alessandro Sperduti, Padua University, Italy
• Hans Weigand, University of Tilburg, The Netherlands
• Mathias Weske, Hasso Plattner Institute at University of Potsdam, Germany

• BPI 2013
• BPI 2012
• BPI 2011
• BPI 2010
• BPI 2009
• BPI 2008
• BPI 2007
• BPI 2006
• BPI 2005