17th International Conference on Principles of Knowledge Representation and Reasoning

Knowledge Graph Inference using Tensor Embedding

Ankur Padia, Kostantinos Kalpakis, Francis Ferraro, and Tim Finin

September 12, 2020

Axiom based inference provides a clear and consistent way of reasoning to add more information to a knowledge graph. However, constructing a set of axioms is expensive and requires domain expertise, time, and money. It is also difficult to reuse or adapt a set of axioms to a knowledge graph in a new domain or even in the same domain but using a slightly different representation approach. This work makes three main contributions, it (1) provides a family of representation learning algorithms and an extensive analysis on eight datasets; (2) yields better results than existing tensor and neural models; and (3) includes a provably convergent factorization algorithm.

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Tags: graph embeddings, knowledge graph, relation inference, tensor decomposition

Type: InProceedings

Publisher: AAAI Press

Note: Recently Published Research Track

Downloads: 531 downloads