Link Prediction in Social Networks: the State-of-the-Art

TL;DR

This paper provides a comprehensive review of the current state-of-the-art methods, challenges, and applications of link prediction in social networks, highlighting recent advances and future research directions.

Contribution

It offers a systematic categorization and analysis of link prediction techniques, problems, and applications in social networks, summarizing recent research achievements.

Findings

Systematic categorization of link prediction techniques

Analysis of challenges and open problems

Overview of applications and future directions

Abstract

In social networks, link prediction predicts missing links in current networks and new or dissolution links in future networks, is important for mining and analyzing the evolution of social networks. In the past decade, many works have been done about the link prediction in social networks. The goal of this paper is to comprehensively review, analyze and discuss the state-of-the-art of the link prediction in social networks. A systematical category for link prediction techniques and problems is presented. Then link prediction techniques and problems are analyzed and discussed. Typical applications of link prediction are also addressed. Achievements and roadmaps of some active research groups are introduced. Finally, some future challenges of the link prediction in social networks are discussed.