2010
DOI: 10.1016/j.eswa.2009.05.010
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Obtaining the consensus and inconsistency among a set of assertions on a qualitative attribute

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Cited by 4 publications
(10 citation statements)
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“…Thus, if for some reason we discard observation d(perhaps because it is the greatest outlier (Guzman-Arenas & Jimenez, 2010), the ''most far away" report), we have, for bag {a, b, c, e}: the total confusion when a is used as candidate for the consensus of {a, b, c, e} is 0 + 0.3 + 0.167 + 0.3 = 0.767; when using b, it is 0.633 + 0 + 0.567 + 0 = 1.2; using c is used as candidate, the total confusion is 0.233 + 0.3 + 0 + 0.3 = 0.833. Finally, using e, it is 0.633 + 0 + 0.567 + 0 = 1.2.…”
Section: Consensus (Most Likely Object) and Inconsistency Of A Bag Ofmentioning
confidence: 97%
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“…Thus, if for some reason we discard observation d(perhaps because it is the greatest outlier (Guzman-Arenas & Jimenez, 2010), the ''most far away" report), we have, for bag {a, b, c, e}: the total confusion when a is used as candidate for the consensus of {a, b, c, e} is 0 + 0.3 + 0.167 + 0.3 = 0.767; when using b, it is 0.633 + 0 + 0.567 + 0 = 1.2; using c is used as candidate, the total confusion is 0.233 + 0.3 + 0 + 0.3 = 0.833. Finally, using e, it is 0.633 + 0 + 0.567 + 0 = 1.2.…”
Section: Consensus (Most Likely Object) and Inconsistency Of A Bag Ofmentioning
confidence: 97%
“…The inconsistencyof a bag of values is reported elsewhere (Guzman-Arenas & Jimenez, 2010); this section is placed here for completeness, in order to understand Section 2.…”
Section: Measuring the Degree Of Inconsistency Of A Bag Of Qualitativmentioning
confidence: 99%
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