Survey on graph embeddings and their applications to machine learning problems on graphs

Survey on graph embeddings and their applications to machine learning problems on graphs

Dealing with relational data always required significant computational resources, domain expertise and task-dependent feature engineering to incorporate structural information into a predictive model. Nowadays, a family of automated graph feature engineering techniques has been proposed in different...

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Bibliographic Details
Main Authors: Ilya Makarov, Dmitrii Kiselev, Nikita Nikitinsky, Lovro Subelj
Format: Article
Language:English
Published: PeerJ Inc. 2021-02-01
Series:PeerJ Computer Science
Subjects:
Graph embedding
Knowledge representation
Machine learning
Network science
Geometric deep learning
Graph neural networks
Online Access:https://peerj.com/articles/cs-357.pdf

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https://peerj.com/articles/cs-357.pdf

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