Personalized Linguistic Information: A Framework of Granular Computing

被引:0
作者
Cabrerizo, F. J. [1 ]
Morente-Molinera, J. A. [1 ]
Alonso, S. [1 ]
Urena, R. [2 ]
Herrera-Viedma, E. [1 ]
机构
[1] Univ Granada, Andalusian Res Inst Data Sci & Computat Intellige, Granada 18071, Spain
[2] De Montfort Univ, Inst Artificial Intelligence, Sch Comp Sci & Informat, Leicester LE1 9BH, Leics, England
来源
PROCEEDINGS OF THE 11TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT 2019) | 2019年 / 1卷
关键词
Group decision making; Linguistic information; Granular computing; GROUP DECISION-MAKING; NUMERICAL SCALE; MODEL; QUALITY; CONSENSUS; EVALUATE; PSO;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In group decision making, the usage of linguistic information entails the requirement for computing with words, a methodology in which words from a natural language are the computational elements. Recently, a new approach based on a framework of granular computing has been applied to cope with linguistic information. Its advantage is that the distribution and the semantics of the linguistic values that represent the words, in place of being defined a priori, are established as defined by the optimization of a given optimization criterion. Once they have been obtained, the distribution and the semantics of the linguistic values are the same for all de decision makers involved in the decision problem. However, as a word means a different thing to different people, we present in this contribution a new approach that is able to obtain personalized linguistic values.
引用
收藏
页码:297 / 304
页数:8
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