Measuring Conflict in a Multi-Source Environment as a Normal Measure

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Wei, Pan; Ball, John E.; Anderson, Derek T.; Harsh, Archit; Archibald, Christopher;
(2018)
  • Subject: Electrical Engineering and Systems Science - Image and Video Processing | Computer Science - Computer Vision and Pattern Recognition | Electrical Engineering and Systems Science - Signal Processing | Computer Science - Artificial Intelligence

In a multi-source environment, each source has its own credibility. If there is no external knowledge about credibility then we can use the information provided by the sources to assess their credibility. In this paper, we propose a way to measure conflict in a multi-so... View more
  • References (10)

    [1] A. Baraka, G. Panoutsos, M. Mahfouf, and S. Cater, “A shannon entropy-based conflict measure for enhancing granular computing-based information processing,” in Granular Computing (GrC), 2014 IEEE International Conference on, Oct 2014, pp. 13-18.

    [2] R. Giordano, “A fuzzy conflict measure for conflict dissolution in drought management,” in Computational Intelligence for Measurement Systems and Applications (CIMSA), 2010 IEEE International Conference on, Sept 2010, pp. 60-65.

    [3] A. Martin, A.-L. Jousselme, and C. Osswald, “Conflict measure for the discounting operation on belief functions,” in Information Fusion, 2008 11th International Conference on, June 2008, pp. 1-8.

    [4] J. C. Gower, “A general coefficient of similarity and some of its properties,” Biometrics, pp. 857-871, 1971.

    [5] P. Zezula, G. Amato, V. Dohnal, and M. Batko, Similarity search: the metric space approach. Springer Science & Business Media, 2006, vol. 32.

    [6] C. Wagner and D. Anderson, “Extracting meta-measures from data for fuzzy aggregation of crowd sourced information,” in Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on, June 2012, pp. 1-8.

    [7] T. Havens, D. Anderson, C. Wagner, H. Deilamsalehy, and D. Wonnacott, “Fuzzy integrals of crowd-sourced intervals using a measure of (a) Measurement from four temperature sensors. generalized accord,” in Fuzzy Systems (FUZZ), 2013 IEEE International Conference on, July 2013, pp. 1-8.

    [8] T. Havens, D. Anderson, and C. Wagner, “Constructing meta-measures from data-informed fuzzy measures for fuzzy integration of interval inputs and fuzzy number inputs,” Fuzzy Systems, IEEE Transactions on, November 2014.

    [9] L. Garmendia, “The evolution of the concept of fuzzy measure,” in Intelligent Data Mining. Springer, 2005, pp. 185-200.

    [10] M. Grabisch, T. Murofushi, and M. Sugeno, Fuzzy Measures and Integrals: Theory and Applications. New York: Physica-Verlag, 2000.

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