Abstract
We introduce the data fusion problem and carefully distinguish it from a number of closely problems. Some of the considerations and knowledge that must go into the development of a multi-source data fusion algorithm are described. We discuss some features that help in expressing users requirements are also described. We provide a general framework for data fusion based on a voting like process that tries to adjudicate conflict among the data. We discuss various of compatibility relations and introduce several examples of these relationships. We consider the case in which the sources have different credibility weight. We introduce the idea of reasonableness as a means for including in the fusion process any information available other than that provided by the sources.
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R. Yager, R. Some Considerations in Multi-Source Data Fusion. In: Ruan, D., Chen, G., E. Kerre, E., Wets, G. (eds) Intelligent Data Mining. Studies in Computational Intelligence, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11004011_1
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DOI: https://doi.org/10.1007/11004011_1
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26256-5
Online ISBN: 978-3-540-32407-2
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