Abstract
When evidence comes from multiple events they should be handled independently, and it is unknown to which event a piece of evidence is related. In this paper, the problem of clustering all pieces of evidence is analyzed systematically to separate them into subsets for each event on the basis of considering the describing format of evidence and making full use of the distance of evidence. An approach for evidence clustering using distance of evidence is presented based on the criterion for clustering. In the proposed approach, the method which is used to establish the initialization of clustering is discussed in detail, called an improved optimal distance. And the centroid vector of evidence and the clustering process are developed respectively to obtain the performance of this novel approach. Finally, an illustrative example shows that this approach is feasible and effective.
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Supported by the National Natural Science Foundation of China (No.60772006).
Communication author: Ye Qing, born in 1978, male, Ph.D.
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Ye, Q., Wu, X. & Chen, Z. An approach for evidence clustering using generalized distance. J. Electron.(China) 26, 18–23 (2009). https://doi.org/10.1007/s11767-008-0122-8
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DOI: https://doi.org/10.1007/s11767-008-0122-8