Learning structured embeddings of knowledge graphs with generative adversarial framework

作者：

Highlights：

• A generative adversarial framework for learning knowledge graph embeddings.

• Easy integration with other neural network systems designed for downstream tasks.

• Significantly improve the performance of link prediction and triple classification.

摘要

•A generative adversarial framework for learning knowledge graph embeddings.•Easy integration with other neural network systems designed for downstream tasks.•Significantly improve the performance of link prediction and triple classification.

论文关键词：Structured embedding learning,Knowledge graph,Generative adversarial network,Triple classification,Link prediction

论文评审过程：Received 14 July 2021, Revised 26 November 2021, Accepted 25 April 2022, Available online 10 May 2022, Version of Record 9 June 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117361