Home
Scholarly Works
A Distributed Link Prediction Algorithm Based on...
Conference

A Distributed Link Prediction Algorithm Based on Clustering in Dynamic Social Networks

Abstract

Link prediction in network attempts to predict the exist-yet-unknown links or future links in accordance with the node properties and the network typology. It has been used in many domains such as social network, biology experiment, and criminal investigations. Classical methods are based on graph topology structure and path features but few consider clustering information. Actually, clustering information plays an important role in link prediction, it connects the sparse nodes and other communities to form intensive communities. Besides the application of clustering, the MapReduce-based method is used to improve the efficiency. The validity of algorithm is verified by real-world datasets. The experimental results show that the proposed algorithm has a higher prediction accuracy and lower time complexity, and is more scalable than traditional methods executed by a single machine.

Authors

Yuan H; Ma Y; Zhang F; Liu M; Shen W

Pagination

pp. 1341-1345

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

January 12, 2016

DOI

10.1109/smc.2015.238

Name of conference

2015 IEEE International Conference on Systems, Man, and Cybernetics
View published work (Non-McMaster Users)

Contact the Experts team