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• Knowledge Graph Representation; From Recent Models towards a Theoretical Understanding

Knowledge Graph Representation

• 1/27/2021 New Technologies in Mathematics
• Speaker(s): Carl Allen and Ivana Balažević, Univ. of Edinburgh School of Informatics
• Title: Knowledge Graph Representation: From Recent Models towards a Theoretical Understanding.

Abstract

Knowledge graphs (KGs), or knowledge bases, are large repositories of facts in the form of triples (subject, relation, object), e.g. (Edinburgh, capital_of, Scotland). Many models have been developed to succinctly represent KGs such that known facts can be recalled (question answering) and, more impressively, previously unknown facts can be inferred (link prediction). Subject and object entities are typically represented as vectors in R^d and relations as mappings (e.g. linear transformations) between them. Such representation can be interpreted as positioning entities in a space such that relations are implied by their relative locations. In this talk we give an overview of knowledge graph representation including select recent models; and, by drawing a connection to word embeddings, explain a theoretical model for how semantic relationships can correspond to geometric structure.