A review of knowledge graph embedding methods of TransE, TransH and TransR for missing links
Knowledge representation and reasoning require knowledge graph embedding as it is crucial in the area. It involves mapping entities and relationships from a knowledge graph into vectors of lower dimensions that are continuous in nature. This encoding enables machine learning algorithms to effectivel...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2023
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/40733/1/A%20Review%20of%20Knowledge%20Graph%20Embedding%20Methods.pdf http://umpir.ump.edu.my/id/eprint/40733/2/A%20review%20of%20knowledge%20graph%20embedding%20methods%20of%20TransE.pdf http://umpir.ump.edu.my/id/eprint/40733/ https://doi.org/10.1109/ICSECS58457.2023.10256354 |
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