Representation of Uncertain Knowledge in Probabilistic OLAP Model

Authors:
Maciej Kiewra
Affiliations:
Institute of Information Science and Engineering, Wroclaw University of Technology, Wrocław, Poland 50-370
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Year:
2008

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Abstract

The probabilistic OLAP model has been presented in this paper. It permits uncertain knowledge to be represented in data warehouse systems. There are two types of uncertainty that can be expressed in this model: imprecise facts and uncertain facts. The former are facts that have occurred but their characteristics are not certain. The latter are facts whose occurrences are uncertain. Typical OLAP algebra operators (set operators, restriction, projection etc.) are included in this model.