Fuzzy and neutrosophic modeling for link prediction in social networks

被引：31

作者：

Tuan, Tran Manh ^{[1
]}

Chuan, Pham Minh ^{[2
]}

Ali, Mumtaz ^{[3
]}

Ngan, Tran Thi ^{[1
]}

Mittal, Mamta ^{[4
]}

Son, Le Hoang ^{[5
]}

机构：

[1] Thuyloi Univ, 175 Tay Son, Hanoi, Vietnam

[2] Hung Yen Univ Technol & Educ, Hung Yen, Vietnam

[3] Univ Southern Queensland, Toowoomba, Qld 4300, Australia

[4] Govind Ballabh Pant Engn Coll, Phase 3, New Delhi, India

[5] Vietnam Natl Univ, VNU Informat Technol Inst, Hanoi, Vietnam

来源：

EVOLVING SYSTEMS | 2019年 / 10卷 / 04期

关键词：

Co-authorship network; Link prediction; Social networks; Fuzzy similarity measures; Neutrosophic measures; CONCEPT LATTICE; SETS; REPRESENTATION;

D O I：

10.1007/s12530-018-9251-y

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Some new similarity measures for link prediction based on fuzzy and neutrosophic environments are proposed. It aims to determine possible association between two objects in a social network represented by a graph including nodes and edges. It is widely used in various domains such as in the co-authorship network and protein-interaction systems. Similarity measure is an important tool for such the determination. Herein, some new fuzzy and neutrosophic measures are proposed accompanied with mathematical properties. The validation on the co-authorship network datasets demonstrates the efficiency of the proposed method.

引用

页码：629 / 634

页数：6

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