Anytime bottom-up rule learning for large-scale knowledge graph completion
Christian Meilicke,
Melisachew Wudage Chekol,
Patrick Betz
et al.
Abstract:Knowledge graph completion is the task of predicting correct facts that can be expressed by the vocabulary of a given knowledge graph, which are not explicitly stated in that graph. Broadly, there are two main approaches for solving the knowledge graph completion problem. Sub-symbolic approaches embed the nodes and/or edges of a given graph into a low-dimensional vector space and use a scoring function to determine the plausibility of a given fact. Symbolic approaches learn a model that remains within the prim… Show more
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