Link Trustworthiness Evaluation over Multiple Heterogeneous Information Networks. (8th March 2021)

• Record Type: Journal Article
• Authors: Wang, Meng; Qin, Xu; Jiang, Wei; Li, Chunshu; Qi, Guilin
• Other Names: Li Jianxin Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-03-08
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/6615179
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Link trustworthiness evaluation is a crucial task for information networks to evaluate the probability of a link being true in a heterogeneous information network (HIN). This task can significantly influence the effectiveness of downstream analysis. However, the performance of existing evaluation methods is limited, as they can only utilize incomplete or one-sided information from a single HIN. To address this problem, we propose a novel multi-HIN link trustworthiness evaluation model that leverages information across multiple related HINs to accomplish link trustworthiness evaluation tasks inherently and efficiently. We present an effective method to evaluate and select informative pairs across HINs and an integrated training procedure to balance inner-HIN and inter-HIN trustworthiness. Experiments on a real-world dataset demonstrate that our proposed model outperforms baseline methods and achieves the best accuracy and F 1-score in downstream tasks of HINs.