• DOI:10.1145/2806416.2806502
Corpus ID: 207228784

Learning to Represent Knowledge Graphs with Gaussian Embedding

@article{He2015LearningTR,
  title={Learning to Represent Knowledge Graphs with Gaussian Embedding},
  author={Shizhu He and Kang Liu and Guoliang Ji and Jun Zhao},
  journal={Proceedings of the 24th ACM International on Conference on Information and Knowledge Management},
  year={2015}
}

Shizhu He, Kang Liu, +1 author Jun Zhao

Published 2015

Computer Science

Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

The representation of a knowledge graph (KG) in a latent space recently has attracted more and more attention. [...] Key Method Each entity/relation is represented by a Gaussian distribution, where the mean denotes its position and the covariance (currently with diagonal covariance) can properly represent its certainty.Expand Abstract

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