Linguistic Representation by Fuzzy Formal Concept and Interval Type-2 Feature Selection

被引：1

作者：

Cherif, Sahar ^{[1
]}

Baklouti, Nesrine ^{[1
]}

Alimi, Adel M. ^{[1
]}

Snasel, Vaclav ^{[2
]}

机构：

[1] Natl Engn Sch Sfax, REGIM Lab REs Grp Intelligent Machines, Sfax, Tunisia

[2] Fac Elect Engn & Comp Sci, Dept Comp Sci, Ostrava, Czech Republic

来源：

INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS (ISDA 2016) | 2017年 / 557卷

关键词：

Fuzzy formal concept; IT-2; FSs; Feature selection; Concept lattice; WORDS; LOGIC; SETS;

D O I：

10.1007/978-3-319-53480-0_105

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Natural language is always seen as a source of uncertainty and vagueness. Fuzzy logic (FL) is a powerful tool for representing and treating perceptions which are the inputs and outputs of a linguistic model. In fact, a linguistic representation is a methodology that moves from crisp measures to uncertain words or fuzzy concepts. This theory uses fuzzy sets to encode and represent linguistic concepts. In this paper, an interval type-2 fuzzy formal concept IT-2FFC is presented as a new approach for extracting knowledge in a linguistic model. The method represents a combination of two techniques: fuzzy formal concept (FFC) for visualizing data and interval type-2 fuzzy sets (IT-2FSs) for feature selection. The obtained results demonstrate that the method applied can help human to make subjective judgments and make decision in a knowledge model.

引用

页码：1071 / 1081

页数：11

共 16 条

[1] Belohlavek R, 2011, CONCEPTS AND FUZZY LOGIC, P1
[2] Concepts and fuzzy sets: Misunderstandings, misconceptions, and oversights
Belohlavek, Radim
Klir, George J.
Lewis, Harold W., III
Way, Eileen C.
[J]. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2009, 51 (01) : 23 - 34
[3] Cherif S., 2014, 6 INT C SOFT COMP PA, P471
[4] A Type-2 Fuzzy Concepts Lexicalized Representation by Perceptual Reasoning and Linguistic Weighted Average: A Comparative Study
Cherif, Sahar
Baklouti, Nesrine
Alimi, Adel M.
Snasel, Vaclav
[J]. HYBRID INTELLIGENT SYSTEMS, HIS 2015, 2016, 420 : 77 - 86
[5] Ontology-based concept similarity in Formal Concept Analysis
Formica, Anna
[J]. INFORMATION SCIENCES, 2006, 176 (18) : 2624 - 2641
[6] A new FCA algorithm enabling analyzing of complex and dynamic data sets
Gajdos, Petr
Snasel, Vaclav
[J]. SOFT COMPUTING, 2014, 18 (04) : 683 - 694
[7] Ganter B., 1997, FORMAL CONCEPT ANAL
[8] Linguistic summaries of data using fuzzy logic
Kacprzyk, J
Yager, RR
[J]. INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2001, 30 (02) : 133 - 154
[9] Lackoff G., 1972, J PHILOS LOGIC, V2, P458
[10] A fuzzy conceptualization model for text mining with application in opinion polarity classification
Li, Sheng-Tun
Tsai, Fu-Ching
[J]. KNOWLEDGE-BASED SYSTEMS, 2013, 39 : 23 - 33

← 1 2 →