Fudge: Fuzzy ontology building with consensuated fuzzy datatypes

被引：9
|
作者：
Huitzil, Ignacio [1 ]
Bobillo, Fernando [1 ,2 ]
Gomez-Romero, Juan [3 ]
Straccia, Umberto [4 ]
机构：
[1] Univ Zaragoza, Zaragoza, Spain
[2] Aragon Inst Engn Res I3A, Zaragoza, Spain
[3] Univ Granada, Granada, Spain
[4] ISTI CNR, Pisa, Italy
来源：
FUZZY SETS AND SYSTEMS | 2020年 / 401卷
关键词：
Fuzzy ontologies; Aggregation operators; Information fusion; GROUP DECISION-MAKING; AGGREGATION OPERATORS; DESCRIPTION LOGICS; INFORMATION; OWL; RECOGNITION; EXTENSION;
D O I：
10.1016/j.fss.2020.04.001
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
An important problem in Fuzzy OWL 2 ontology building is the definition of fuzzy membership functions for real-valued fuzzy sets (so-called fuzzy datatypes in Fuzzy OWL 2 terminology). In this paper, we present a tool, called Fudge, whose aim is to support the consensual creation of fuzzy datatypes by aggregating the specifications given by a group of experts. Fudge is freeware and currently supports several linguistic aggregation strategies, including the convex combination, linguistic OWA, weighted mean and fuzzy OWA, and easily allows to build others in. We also propose and have implemented two novel linguistic aggregation operators, based on a left recursive form of the convex combination and of the linguistic OWA. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码：91 / 112
页数：22
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