Abstract
In this paper, we describe an extension of the OLAP (On-Line Analytical Processing) framework with automated causal diagnosis, offering the possibility to automatically generate explanations and diagnostics to support business decision tasks. This functionality can be provided by extending the conventional OLAP system with an explanation formalism, which mimics the work of business decision makers in diagnostic processes. The central goal of this paper is the identification of specific knowledge structures and reasoning methods required to construct computerized explanations from multidimensional data and business models. The methodology was tested on a case study involving the comparison of financial results of a firm’s business units.
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© 2005 Springer-Verlag Berlin Heidelberg
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Caron, E., Daniels, H. (2005). Automated business diagnosis in the OLAP context. In: Fleuren, H., den Hertog, D., Kort, P. (eds) Operations Research Proceedings 2004. Operations Research Proceedings, vol 2004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-27679-3_53
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DOI: https://doi.org/10.1007/3-540-27679-3_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24274-1
Online ISBN: 978-3-540-27679-1
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