Knowledge Graph Completion with Adaptive Sparse Transfer Matrix
@inproceedings{Ji2016KnowledgeGC, title={Knowledge Graph Completion with Adaptive Sparse Transfer Matrix}, author={Guoliang Ji and Kang Liu and Shizhu He and Jun Zhao}, booktitle={AAAI}, year={2016} }
We model knowledge graphs for their completion by encoding each entity and relation into a numerical space. All previous work including Trans(E, H, R, and D) ignore the heterogeneity (some relations link many entity pairs and others do not) and the imbalance (the number of head entities and that of tail entities in a relation could be different) of knowledge graphs. In this paper, we propose a novel approach TranSparse to deal with the two issues. In TranSparse, transfer matrices are replaced… CONTINUE READING
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