Knowledge Transfer for Out-of-Knowledge-Base Entities: Improving Graph-Neural-Network-Based Embedding Using Convolutional Layers
Knowledge base completion (KBC) aims to predict missing information in a knowledge base. Most existing embedding-based KBC models assume that all test entities are available at training time. Thus, a question arises-that is, how to answer queries concerning test entities not observed at training tim...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9178374/ |