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- W2977969475 abstract "This poster paper presents an efficient method R-Linker for link prediction in large knowledge graphs, based on rule learning. The scalability and efficiency is achieved by a combination of several optimisation techniques. Experimental results show that R-Linker is able to handle KGs with over 10 million of entities and more efficient than existing state-of-the-art methods including RLvLR and AMIE+ in rule learning stage for link prediction." @default.
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- W2977969475 date "2019-01-01" @default.
- W2977969475 modified "2023-09-23" @default.
- W2977969475 title "A system for reasoning-based link prediction in large knowledge graphs" @default.
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