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...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2019-06-01
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Series: | Data Science and Engineering |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1007/s41019-019-0097-5 |