Complexity-Aware Generation of Workflows by Process-Oriented Case-Based Reasoning View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-09-19

AUTHORS

Gilbert Müller , Ralph Bergmann

ABSTRACT

One of the biggest challenges in business process management is the creation of appropriate and efficient workflows. This asks for intelligent, knowledge-based systems that assist domain experts in this endeavor. In this paper we investigate workflow creation by applying Process-Oriented Case-Based Reasoning (POCBR). We introduce POCBR and describe how it can be applied to the experience-based generation of workflows by retrieval and adaptation of available best-practice workflow models. While existing approaches have already demonstrated their feasibility in principle, the generated workflows are not optimized with respect to complexity requirements. However, there is a high interest in workflows with a low complexity, e.g., to ensure the appropriate enactment as well as the understandability of the workflow. The main contribution of this paper is thus a novel approach to consider the workflow complexity during the workflow generation. Therefore, a complexity measure for workflows is proposed and integrated into the retrieval and adaptation process. An experimental evaluation with real cooking recipes clearly demonstrates the benefits of the described approach. More... »

PAGES

207-221

Book

TITLE

KI 2017: Advances in Artificial Intelligence

ISBN

978-3-319-67189-5
978-3-319-67190-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-67190-1_16

DOI

http://dx.doi.org/10.1007/978-3-319-67190-1_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1091834457


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