Predicting Missing Links Based on a New Triangle Structure
Joint Authors
Cheng, Jianjun
Bai, Shenshen
Xu, Shijin
Chen, Xiaoyun
Li, Longjie
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
With the rapid growth of various complex networks, link prediction has become increasingly important because it can discover the missing information and predict future interactions between nodes in a network.
Recently, the CAR and CCLP indexes have been presented for link prediction by means of different triangle structure information.
However, both indexes may lose the contributions of some shared neighbors.
We propose in this work a new index to make up the weakness and then improve the accuracy of link prediction.
The proposed index focuses on a new triangle structure, i.e., the triangle formed by one seed node, one common neighbor, and one other node.
It emphasizes the importance of these triangles but does not ignore the contribution of any common neighbor.
In addition, the proposed index adopts the theory of resource allocation by penalizing large-degree neighbors.
The results of comparison with CN, AA, RA, ADP, CAR, CAA, CRA, and CCLP on 12 real-world networks show that the proposed index outperforms the compared methods in terms of AUC and ranking score.
American Psychological Association (APA)
Bai, Shenshen& Li, Longjie& Cheng, Jianjun& Xu, Shijin& Chen, Xiaoyun. 2018. Predicting Missing Links Based on a New Triangle Structure. Complexity،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1135733
Modern Language Association (MLA)
Bai, Shenshen…[et al.]. Predicting Missing Links Based on a New Triangle Structure. Complexity No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1135733
American Medical Association (AMA)
Bai, Shenshen& Li, Longjie& Cheng, Jianjun& Xu, Shijin& Chen, Xiaoyun. Predicting Missing Links Based on a New Triangle Structure. Complexity. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1135733
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1135733