Papers with Bayesian network structures

1 papers
Learning Interpretable Relationships between Entities, Relations and Concepts via Bayesian Structure Learning on Open Domain Facts (2020.acl-main)

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Challenge: Concept graphs are created as universal taxonomies for text understanding in the open domain knowledge.
Approach: They propose to learn interpretable relationships from open-domain facts to enrich concept graphs.
Outcome: The proposed method improves the identification of concepts for entities based on relations between entities on public English and Chinese datasets.

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