Representation Learning of Knowledge Graphs with Embedding Subspaces
Most of the existing knowledge graph embedding models are supervised methods and largely relying on the quality and quantity of obtainable labelled training data. The cost of obtaining high quality triples is high and the data sources are facing a serious problem of data sparsity, which may result i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2020-01-01
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| Series: | Scientific Programming |
| Online Access: | http://dx.doi.org/10.1155/2020/4741963 |