Bipolar fuzzy graph representation of concept lattice

被引：103
|
作者：
Singh, Prem Kumar [1 ]
Kumar, Ch. Aswani [1 ]
机构：
[1] VIT Univ, Sch Informat Technol & Engn, Vellore 632014, Tamil Nadu, India
来源：
INFORMATION SCIENCES | 2014年 / 288卷
关键词：
Bipolar fuzzy graph; Bipolar information; Formal concept analysis; Fuzzy concept lattice; Fuzzy formal concept; FORMAL CONCEPT ANALYSIS; MODEL; SPACE; SET;
D O I：
10.1016/j.ins.2014.07.038
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Formal Concept Analysis (FCA) is a mathematical framework for knowledge processing tasks. FCA has been successfully incorporated into fuzzy setting and its extension (interval-valued fuzzy set) for handling vagueness and impreciseness in data. However, the analysis in such settings is restricted to unipolar space. Recently, some applications of bipolar information are shown in bipolar fuzzy graph, lattice theory as well as in FCA. The adequate analysis of bipolar information using FCA requires incorporation of bipolar fuzzy set and an appropriate lattice structure. For this purpose, we propose an algorithm for generating the bipolar fuzzy formal concepts, a method for (alpha,beta)-cut of bipolar fuzzy formal context and its implications with illustrative examples. (C)2014 Elsevier Inc. All rights reserved.
引用
收藏
页码：437 / 448
页数：12
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