11 lines
1.9 KiB
Properties
11 lines
1.9 KiB
Properties
#Properties file for afryca.consensusmodel.kacprzyk2010
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Bundle-Vendor = Sinbad\u00B2
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Bundle-Name = Kacprzyk2010
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afryca.consensusmodel.kacprzyk2010.information = Paper: J. Kacprzyk, S. Zadrozny. Supporting consensus reaching processes under fuzzy preferences and a fuzzy majority via linguistic summaries. Studies in Fuzziness and Soft Computing 257 (2010), pp. 149-157.\\n\\nJ. Kacprzyk, S. Zadrozny. Soft computing and web intelligence for supporting consensus reaching. Soft Computing 14(2010), pp. 833-846.\\n\\nConsensus model based on the notion of "soft consensus" under fuzzy preference relations. Similarities between pairs of experts are computed at level of assessment, as alpha-degrees of sufficient agreement. Consensus degrees are obtained at different levels from such similarities, based on quantifier-guided OWA aggregation. The feedback mechanism identifies the pairs of alternatives with lowest degree of agreement, and then generates recommendations for experts.
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afryca.consensusmodel.kacprzyk2010.mainfeature = Fuzzy preference relations\\n"Soft consensus" measure\\nLinguistic quantifiers\\nalpha-degrees of sufficient agreement
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afryca.consensusmodel.kacprzyk2010.name = J. Kacprzyk et al. (2010)
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afryca.consensusmodel.kacprzyk2010.observations = Instead of using linguistic summaries, the feedback mechanism implemented is based on the criterion "lack of arguments" (see 2nd reference).
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afryca.consensusmodel.kacprzyk2010.variable.h_max.description = Maximum number of discussion rounds allowed
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afryca.consensusmodel.kacprzyk2010.variable.aggregation_quantifiers.description = Parameters of the linguistic quantifier used in the aggregation process to compute consensus
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afryca.consensusmodel.kacprzyk2010.variable.alpha.description = Parameter used for the non-strict similarity measure between experts' assessments
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afryca.consensusmodel.kacprzyk2010.variable.cl.description = Consensus threshold |