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2013 IEEE 37th Annual Computer Software and Applications Conference (2002)
Oxford, England
Aug. 26, 2002 to Aug. 29, 2002
ISSN: 0730-3157
ISBN: 0-7695-1727-7
pp: 1129
Roman Slowinski , Poznan University of Technology
Salvatore Greco , University of Catania
Benedetto Matarazzo , University of Catania
Given a ranking of actions evaluated by a set of evaluation criteria, we are constructing a rough approximation of the preference relation known from this ranking. The rough approximation of the preference relation is a starting point for mining "if…, then…" decision rules constituting a symbolic preference model. The set of rules is induced such as to be compatible with a concordance-discordance preference model used in well-known multicriteria decision aiding methods. Application of the set of decision rules to a new set of actions gives a fuzzy outranking graph. Positive and negative flows are calculated for each action in the graph, giving arguments about its strength and weakness. Aggregation of both arguments leads to a final ranking, either partial or complete. The approach can be applied to support multicriteria choice and ranking of actions when the input information is a ranking of some reference actions.
Roman Slowinski, Salvatore Greco, Benedetto Matarazzo, "Mining Decision-Rule Preference Model from Rough Approximation of Preference Relation", 2013 IEEE 37th Annual Computer Software and Applications Conference, vol. 00, no. , pp. 1129, 2002, doi:10.1109/CMPSAC.2002.1045163
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