A survey of link prediction in complex networks
Networks have become increasingly important to model complex systems composed of
interacting elements. Network data mining has a large number of applications in many …
interacting elements. Network data mining has a large number of applications in many …
Adaptive degree penalization for link prediction
Many systems of interest are best described using networks that represent binary
relationships among their elements. Link prediction aims to infer the link formation process …
relationships among their elements. Link prediction aims to infer the link formation process …
Exploring social networks through stochastic multilayer graph modeling
Several graph models are available today to model online social networks. These graph
models are used to analyze the structural properties of the online social network, such as …
models are used to analyze the structural properties of the online social network, such as …
Link prediction using thresholding nodes based on their degree
In this chapter, we propose MIDT, a degree threshold-based similarity measure, for link
prediction which exploits the power law degree distribution which social networks typically …
prediction which exploits the power law degree distribution which social networks typically …
A Review of Similarity Measures and Link Prediction Models in Social Networks.
Social network is a web-based platform which enables people to share information, make
new connections and explore various events that occur in society. In social networks, link …
new connections and explore various events that occur in society. In social networks, link …
Recommender engines under the influence of popularity
G Blot, P Saurel, F Rousseaux - International Conference on E …, 2015 - Springer
One often thinks that the use of Information Technologies brings an infinity of choices.
However, Popularity still influences people in our free, pervasive and connected world. It is a …
However, Popularity still influences people in our free, pervasive and connected world. It is a …
An Investigation of Attention Mechanisms in Graph Convolutional Networks applied to Link Prediction Problems
R Li - 2020 - repository.library.carleton.ca
The link prediction problem is fundamental to many application domains. Recently, deep
learning-based models have been proposed to tackle this kind of problem. Graph auto …
learning-based models have been proposed to tackle this kind of problem. Graph auto …
Two-phase approach to link prediction
Link prediction deals with predicting edges which are likely to occur in the future. The
clustering coefficient of sparse networks is typically small. Link prediction performs poorly on …
clustering coefficient of sparse networks is typically small. Link prediction performs poorly on …