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Learning preferences from paired opposite-based semantics

Publikation: Forskning - peer reviewTidsskriftartikel

Standard

Learning preferences from paired opposite-based semantics. / Franco de los Ríos, Camilo; Rodríguez, J. Tinguaro; Montero, Javier.

I: International Journal of Approximate Reasoning, Bind 86, 2017, s. 80-91.

Publikation: Forskning - peer reviewTidsskriftartikel

Harvard

Franco de los Ríos, C, Rodríguez, JT & Montero, J 2017, 'Learning preferences from paired opposite-based semantics' International Journal of Approximate Reasoning, bind 86, s. 80-91. DOI: 10.1016/j.ijar.2017.04.010

APA

Franco de los Ríos, C., Rodríguez, J. T., & Montero, J. (2017). Learning preferences from paired opposite-based semantics. International Journal of Approximate Reasoning, 86, 80-91. DOI: 10.1016/j.ijar.2017.04.010

Vancouver

Franco de los Ríos C, Rodríguez JT, Montero J. Learning preferences from paired opposite-based semantics. International Journal of Approximate Reasoning. 2017;86:80-91. Tilgængelig fra, DOI: 10.1016/j.ijar.2017.04.010

Author

Franco de los Ríos, Camilo ; Rodríguez, J. Tinguaro ; Montero, Javier. / Learning preferences from paired opposite-based semantics. I: International Journal of Approximate Reasoning. 2017 ; Bind 86. s. 80-91

Bibtex

@article{b572cb2882f84774ad7fb7e98369e4a9,
title = "Learning preferences from paired opposite-based semantics",
abstract = "Preference semantics examine the meaning of the preference predicate, according to the way that alternatives can be understood and organized for decision making purposes. Through opposite-based semantics, preference structures can be characterized by their paired decomposition of preference into opposite poles, and their respective valuation of binary preference relations. Extending paired semantics by fuzzy sets, preference relations can be represented in a gradual functional form, under an enhanced representational frame for examining the meaning of preference. Following a semantic argument on the character of opposition, the compound meaning of preference emerges from the fuzzy reinforcement of paired opposite concepts, searching for significant evidence for affirming dominance among the decision objects. Here we propose a general model for the paired decomposition of preference, examining its characteristic semantics under a binary and fuzzy logical frame, and identifying solutions with different values of significance for preference learning.",
keywords = "Fuzzy logic, Fuzzy reinforcement, Paired concepts, Preference structures, Semantic opposition, Significance",
author = "{Franco de los Ríos}, Camilo and Rodríguez, {J. Tinguaro} and Javier Montero",
year = "2017",
doi = "10.1016/j.ijar.2017.04.010",
volume = "86",
pages = "80--91",
journal = "International Journal of Approximate Reasoning",
issn = "0888-613X",
publisher = "Elsevier Inc.",

}

RIS

TY - JOUR

T1 - Learning preferences from paired opposite-based semantics

AU - Franco de los Ríos,Camilo

AU - Rodríguez,J. Tinguaro

AU - Montero,Javier

PY - 2017

Y1 - 2017

N2 - Preference semantics examine the meaning of the preference predicate, according to the way that alternatives can be understood and organized for decision making purposes. Through opposite-based semantics, preference structures can be characterized by their paired decomposition of preference into opposite poles, and their respective valuation of binary preference relations. Extending paired semantics by fuzzy sets, preference relations can be represented in a gradual functional form, under an enhanced representational frame for examining the meaning of preference. Following a semantic argument on the character of opposition, the compound meaning of preference emerges from the fuzzy reinforcement of paired opposite concepts, searching for significant evidence for affirming dominance among the decision objects. Here we propose a general model for the paired decomposition of preference, examining its characteristic semantics under a binary and fuzzy logical frame, and identifying solutions with different values of significance for preference learning.

AB - Preference semantics examine the meaning of the preference predicate, according to the way that alternatives can be understood and organized for decision making purposes. Through opposite-based semantics, preference structures can be characterized by their paired decomposition of preference into opposite poles, and their respective valuation of binary preference relations. Extending paired semantics by fuzzy sets, preference relations can be represented in a gradual functional form, under an enhanced representational frame for examining the meaning of preference. Following a semantic argument on the character of opposition, the compound meaning of preference emerges from the fuzzy reinforcement of paired opposite concepts, searching for significant evidence for affirming dominance among the decision objects. Here we propose a general model for the paired decomposition of preference, examining its characteristic semantics under a binary and fuzzy logical frame, and identifying solutions with different values of significance for preference learning.

KW - Fuzzy logic

KW - Fuzzy reinforcement

KW - Paired concepts

KW - Preference structures

KW - Semantic opposition

KW - Significance

U2 - 10.1016/j.ijar.2017.04.010

DO - 10.1016/j.ijar.2017.04.010

M3 - Journal article

VL - 86

SP - 80

EP - 91

JO - International Journal of Approximate Reasoning

T2 - International Journal of Approximate Reasoning

JF - International Journal of Approximate Reasoning

SN - 0888-613X

ER -

ID: 182090353