A formal model for process context learning

Johny Ghattas, Pnina Soffer, Mor Peleg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Process models are considered to be a major asset in modern business organizations. They are expected to apply to all the possible business contexts in which the process may be executed, however not all of these are known a priori. Instead of identifying all contexts before the process is established, we propose to learn from runtime experience which contextual properties should be taken into account by the process model. We propose a model and an associated procedure for identifying and learning the relevant context categories of a process out of runtime experience. We postulate that the context of a process, namely, properties of the specific business case and environmental events, affects its execution and outcomes. However, when a process is launched, the exact effect and affecting variables are not necessarily known. Our approach aims at categorizing possible environmental conditions and case properties into context categories which are meaningful for the process execution. This is achieved by a context learning framework, presented in the paper.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops - BPM 2009 International Workshops, Revised Papers
PublisherSpringer Verlag
Number of pages18
ISBN (Print)3642121853, 9783642121852
StatePublished - 2010
EventBusiness Process Management Workshops - BPM 2009 International Workshops - Ulm, Germany
Duration: 7 Sep 20097 Sep 2009

Publication series

NameLecture Notes in Business Information Processing
Volume43 LNBIP
ISSN (Print)1865-1348


ConferenceBusiness Process Management Workshops - BPM 2009 International Workshops


  • Business process context
  • Business process learning
  • Flexibility
  • Process goals
  • Process model adaptation
  • Soft-goals

ASJC Scopus subject areas

  • Management Information Systems
  • Control and Systems Engineering
  • Business and International Management
  • Information Systems
  • Modeling and Simulation
  • Information Systems and Management


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