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Cross Organisational Compatible Plans Generation Framework

Saleem, Mohammad and Chung, Paul W. H and Fatima, Shaheen and Dai, Wei (2011) Cross Organisational Compatible Plans Generation Framework. In: Research and Development in Intelligent Systems XXVIII: Incorporating Applications and Innovations in Intelligent Systems XIX. Bramer, Max and Petridis, Miltos and Nolle, Lars, eds. Research and development in intelligent systems series (28). Springer, London, pp. 223-228.

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Abstract

In this modern era, organisations have to work in coordination with many other organisations in order to succeed in business. Interacting organisations can only proceed in business if they have compatible workflows. This paper proposes a framework to automatically generate compatible workflows for multiple interacting organisations from their process definitions and service descriptions. Existing systems can reconcile existing workflows only, and cannot generate compatible workflows for multiple organisations automatically. The proposed system is different from existing systems since it targets workflow collaboration by generating workflows automatically. This allows the organisations to save the time that would otherwise be spent in modelling workflows and making them compatible with the workflows of interacting organisations.

Item Type: Book Section
ISBN: 9781447123170 (print) 9781447123187 (online)
Additional Information:

Proceedings of AI-2011, the Thirty-first SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence

Uncontrolled Keywords: ResPubID23825, generation framework, workflow collaboration, compatible workflows, interacting organisations
Subjects: Faculty/School/Research Centre/Department > School of Management and Information Systems
FOR Classification > 0806 Information Systems
SEO Classification > 8902 Computer Software and Services
Depositing User: VUIR
Date Deposited: 09 Jan 2013 03:00
Last Modified: 09 Jan 2013 03:11
URI: http://vuir.vu.edu.au/id/eprint/9631
DOI: 10.1007/978-1-4471-2318-7_17
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