A Universal Method Based on Structure Subgraph Feature for Link Prediction over Dynamic Networks

2019 ◽  
Author(s):  
Xiao Li ◽  
Wenxin Liang ◽  
Xianchao Zhang ◽  
Xinyue Liu ◽  
Weili Wu
Keyword(s):  
Link Prediction ◽  
Dynamic Networks ◽  
Universal Method

Network embedding based link prediction in dynamic networks

2021 ◽  
Author(s):  
Shashi Prakash Tripathi ◽  
Rahul Kumar Yadav ◽  
Abhay Kumar Rai
Keyword(s):  
Link Prediction ◽  
Dynamic Networks ◽  
Network Embedding

scholarly journals Nonparametric link prediction in large scale dynamic networks

2014 ◽  
Vol 8 (2) ◽  
pp. 2022-2065 ◽  
Author(s):  
Purnamrita Sarkar ◽  
Deepayan Chakrabarti ◽  
Michael Jordan
Keyword(s):  
Link Prediction ◽  
Large Scale ◽  
Dynamic Networks

Similarity-Based Indices or Metrics for Link Prediction

2019 ◽  
pp. 1-29
Author(s):  
Praveen Kumar Bhanodia ◽  
Kamal Kumar Sethi ◽  
Aditya Khamparia ◽  
Babita Pandey ◽  
Shaligram Prajapat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Link Prediction ◽  
Online Social Network ◽  
Dynamic Networks ◽  
Relevant Information ◽  
Network Evolution ◽  
Problem Instance ◽  
The Social ◽  
Social Network Evolution

Link prediction in social network has gained momentum with the inception of machine learning. The social networks are evolving into smart dynamic networks possessing various relevant information about the user. The relationship between users can be approximated by evaluation of similarity between the users. Online social network (OSN) refers to the formulation of association (relationship/links) between users known as nodes. Evolution of OSNs such as Facebook, Twitter, Hi-Fi, LinkedIn has provided a momentum to the growth of such social networks, whereby millions of users are joining it. The online social network evolution has motivated scientists and researchers to analyze the data and information of OSN in order to recommend the future friends. Link prediction is a problem instance of such recommendation systems. Link prediction is basically a phenomenon through which potential links between nodes are identified on a network over the period of time. In this chapter, the authors describe the similarity metrics that further would be instrumental in recognition of future links between nodes.

A supervised link prediction method for dynamic networks

2016 ◽  
Vol 31 (1) ◽  
pp. 291-299 ◽  
Author(s):  
Ke-Jia Chen ◽  
Yang Chen ◽  
Yun Li ◽  
Jingyu Han
Keyword(s):  
Link Prediction ◽  
Dynamic Networks ◽  
Prediction Method
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