Business Processes, Dynamic Contexts, Learning

Author:

Richter Michael M.1

Affiliation:

1. University of Calgary, Canada

Abstract

In this article we present relations between complex business processes and machine learning techniques. The processes considered here are mostly related to planning. Planning takes place in preparing many decisions and often it is encountered with a rapidly changing context that constitutes an open world. The underlying structure and preconditions of the processes is quite often not known and hence the processes are regarded as stochastic. One can only observe the processes. Such observations deliver data and these data contain some knowledge about the processes in a hidden form. As a consequence, machine learning methods are involved here. The idea is to give the business persons an overview of quite different machine learning techniques so that they can select suitable ones. We provide a number of examples for business processes that we use for illustrations.

Publisher

IGI Global

Reference12 articles.

1. Managing Global Innovation

2. Extracting Knowledge from Sensor Signals for Case-Based Reasoning with Longitudinal Time Series Data. Article;P.Funk;Case-Based Reasoning on images and signals,2007

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