Abstract
Due to its subjective naturewhich can otherwise compromise the integrity of the fusion process, it is critical that soft evidence (generated by human sources) be validated prior to its incorporation into the fusion engine. The strategy of discounting evidence based on source reliability may not be applicable when dealing with soft sources because their reliability (e.g., an eye witnesses account) is often unknown beforehand. In this paper, we propose a methodology based on the notion of consensus to estimate the credibility of (soft) evidence in the absence of a ‘ground truth.’ This estimated credibility can then be used for source reliability estimation, discounting or appropriately ‘weighting’ evidence for fusion. The consensus procedure is set up via Dempster-Shafer belief theoretic notions. Further, the proposed procedure allows one to constrain the consensus by an estimate of the ground truth if/when it is available. We illustrate several interesting and intuitively appealing properties of the consensus procedure via a numerical example.
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Wickramarathne, T.L., Premaratne, K., Murthi, M.N. (2012). Consensus-Based Credibility Estimation of Soft Evidence for Robust Data Fusion. In: Denoeux, T., Masson, MH. (eds) Belief Functions: Theory and Applications. Advances in Intelligent and Soft Computing, vol 164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29461-7_35
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DOI: https://doi.org/10.1007/978-3-642-29461-7_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29460-0
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