Applications of link prediction in social networks: A review
Link prediction methods anticipate the likelihood of a future connection between two nodes
in a given network. The methods are essential in social networks to infer social interactions …
in a given network. The methods are essential in social networks to infer social interactions …
Formatting biological big data for modern machine learning in drug discovery
M Duran‐Frigola, A Fernández‐Torras… - Wiley …, 2019 - Wiley Online Library
Biological data is accumulating at an unprecedented rate, escalating the role of data‐driven
methods in computational drug discovery. This scenario is favored by recent advances in …
methods in computational drug discovery. This scenario is favored by recent advances in …
Similarity-based future common neighbors model for link prediction in complex networks
S Li, J Huang, Z Zhang, J Liu, T Huang, H Chen - Scientific reports, 2018 - nature.com
Link prediction aims to predict the existence of unknown links via the network information.
However, most similarity-based algorithms only utilize the current common neighbor …
However, most similarity-based algorithms only utilize the current common neighbor …
Pioneering topological methods for network-based drug–target prediction by exploiting a brain-network self-organization theory
The bipartite network representation of the drug–target interactions (DTIs) in a biosystem
enhances understanding of the drugs' multifaceted action modes, suggests therapeutic …
enhances understanding of the drugs' multifaceted action modes, suggests therapeutic …
Cold start similar artists ranking with gravity-inspired graph autoencoders
G Salha-Galvan, R Hennequin, B Chapus… - Proceedings of the 15th …, 2021 - dl.acm.org
On an artist's profile page, music streaming services frequently recommend a ranked list of”
similar artists” that fans also liked. However, implementing such a feature is challenging for …
similar artists” that fans also liked. However, implementing such a feature is challenging for …
Link prediction in heterogeneous information networks: An improved deep graph convolution approach
X Wang, Y Chai, H Li, D Wu - Decision Support Systems, 2021 - Elsevier
Heterogeneous information networks (HINs) refer to logical networks involving entities of
multiple types and their multiple relations, which are widely used for modeling real-world …
multiple types and their multiple relations, which are widely used for modeling real-world …
Mutual Influence in Citation and Cooperation Patterns
Measuring the influence of scientists and their activities on science and society is important
and indeed essential for many studies. Despite the substantial efforts devoted to exploring …
and indeed essential for many studies. Despite the substantial efforts devoted to exploring …
Local-community network automata modelling based on length-three-paths for prediction of complex network structures in protein interactomes, food webs and more
From nests to nets intricate wiring diagrams surround the birth and the death of life. Here we
show that the same rule of complex network self-organization is valid across different …
show that the same rule of complex network self-organization is valid across different …
A potential energy and mutual information based link prediction approach for bipartite networks
Link prediction in networks has applications in computer science, graph theory, biology,
economics, etc. Link prediction is a very well studied problem. Out of all the different …
economics, etc. Link prediction is a very well studied problem. Out of all the different …
Uncovering the dynamics of market convergence through M&A
LJ Aaldering, J Leker, CH Song - Technological Forecasting and Social …, 2019 - Elsevier
Despite the significance of converging markets as a new competitive paradigm to change
how organizations function and produce value, little attention has been devoted to …
how organizations function and produce value, little attention has been devoted to …