Domain-aware trust network extraction for trust propagation in large-scale heterogeneous trust networks

被引:27
|
作者
Jiang, Cuiqing [1 ]
Liu, Shixi [1 ,2 ]
Lin, Zhangxi [3 ]
Zhao, Guozhu [2 ]
Duan, Rui [1 ]
Liang, Kun [1 ]
机构
[1] Hefei Univ Technol, Sch Management, Hefei 230009, Anhui, Peoples R China
[2] Chuzhou Univ, Sch Comp & Informat Engn, Chuzhou 239000, Anhui, Peoples R China
[3] Texas Tech Univ, Rawls Coll Business Adm, Lubbock, TX 79409 USA
基金
中国国家自然科学基金;
关键词
Domain-aware trust network; Heterogeneous trust network; Directed multigraph; Trust propagation; PREDICTION;
D O I
10.1016/j.knosys.2016.08.019
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Because users of online social networks (OSNs) may encounter others whom they have incomplete knowledge of or no previous experience with, trust propagation has become increasingly necessary in many real-world applications. However, trust propagation in extracted trust networks often fails because few studies view trust as domain-dependent. To address this gap in the research, this paper attempts to extract a domain-aware trust network to achieve more accurate trust propagation. A directed multigraph is adopted to model the multiple trust relationships among users in a heterogeneous trust network (HTN). A domain-aware trust metric is then designed to measure the degree of trust between users considering their domain-aware influential power in an OSN. A domain-aware trust network extraction approach is proposed in accordance with the trust model and domain-aware trust metric. Based on a real-world dataset, prevailing trust propagation algorithms are applied in the extracted domain-aware trust network, which validates our domain-aware trust network extraction approach. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:237 / 247
页数:11
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