Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study

Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study

Abstract Graph embeddings have become a key and widely used technique within the field of graph mining, proving to be successful across a broad range of domains including social, citation, transportation and biological. Unsupervised graph embedding techniques aim to automatically create a low-dimens...

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Bibliographic Details
Main Authors: Stephen Bonner, Ibad Kureshi, John Brennan, Georgios Theodoropoulos, Andrew Stephen McGough, Boguslaw Obara
Format: Article
Language:English
Published: SpringerOpen 2019-06-01
Series:Data Science and Engineering
Subjects:
Graph embeddings
Neural networks
Representation learning
Online Access:http://link.springer.com/article/10.1007/s41019-019-0097-5

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