In this paper, we propose a translation model on subgragh representing knowledge graph. The model builds an ensemble TransE model on subgraph divided by features of relations in triplets by training the model with different parts of dataset independently. Afterwards, experimental results on link prediction show improvements on parameters compared to the state-of-the-art baselines.
CITATION STYLE
Tan, Y., Li, R., Zhou, J., & Zhu, S. (2019). Knowledge Graph Embedding by Translation Model on Subgraph. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11354 LNCS, pp. 269–280). Springer Verlag. https://doi.org/10.1007/978-3-030-15127-0_27
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