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
相关论文
共 50 条
  • [41] Rejection and symmetric difference of bipolar picture fuzzy graph
    Almousa, Maha Mohammed
    Tchier, Fairouz
    DEMONSTRATIO MATHEMATICA, 2023, 56 (01)
  • [42] A Clustering Reduction Algorithm for Fuzzy Concept Lattice
    Zhang, Qiangyi
    Qu, Yanpeng
    Deng, Ansheng
    Zwiggelaar, Reyer
    2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), 2017,
  • [43] Cyclic connectivity index of bipolar fuzzy incidence graph
    Lu, Juanjuan
    Zhu, Linli
    Gao, Wei
    OPEN CHEMISTRY, 2022, 20 (01): : 331 - 341
  • [44] Hesitant Fuzzy Concept Lattice and its Application
    Yang, Xue
    Xu, Zeshui
    IEEE ACCESS, 2020, 8 : 59774 - 59786
  • [45] Rough Fuzzy Concept Lattice and Its Properties
    Shu, Chang
    Mo, Zhi-wen
    FUZZY SYSTEMS & OPERATIONS RESEARCH AND MANAGEMENT, 2016, 367 : 163 - 170
  • [46] Unifying Fuzzy Concept Lattice Construction Methods
    Boffa, Stefania
    De Maio, Carmen
    Di Nola, Antonio
    Fenza, Giuseppe
    Ferraioli, Anna Rita
    Loia, Vincenzo
    2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2016, : 209 - 216
  • [47] Construction of the L-fuzzy concept lattice
    Burusco, A
    Fuentes-Gonzalez, R
    FUZZY SETS AND SYSTEMS, 1998, 97 (01) : 109 - 114
  • [48] A Graph-Theoretic Method to Representing a Concept Lattice
    Mao, Hua
    APPLIED MATHEMATICS & INFORMATION SCIENCES, 2014, 8 (02): : 553 - 561
  • [49] Concept Factorization with Optimal Graph Learning for Data Representation
    Shu, Zhenqiu
    Wu, Xiao-jun
    Fan, Honghui
    You, Congzhe
    Liu, Zhen
    Zhang, Jie
    IMAGE AND GRAPHICS, ICIG 2019, PT II, 2019, 11902 : 74 - 84
  • [50] Combining concept lattice with call graph for impact analysis
    Li, Bixin
    Sun, Xiaobing
    Leung, Hareton
    ADVANCES IN ENGINEERING SOFTWARE, 2012, 53 : 1 - 13
12345