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Title: Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders | Proceedings of the AAAI Conference on Artificial Intelligence

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DC.Creator.PersonalNameMathias Niepert
DC.Date.created2021-05-18
DC.Date.dateSubmitted2020-09-10
DC.Date.issued2021-05-28
DC.Date.modified2022-09-08
DC.DescriptionRepresentation learning for knowledge graphs (KGs) has focused on the problem of answering simple link prediction queries. In this work we address the more ambitious challenge of predicting the answers of conjunctive queries with multiple missing entities. We propose Bidirectional Query Embedding (BiQE), a method that embeds conjunctive queries with models based on bi-directional attention mechanisms. Contrary to prior work, bidirectional self-attention can capture interactions among all the elements of a query graph. We introduce two new challenging datasets for studying conjunctive query inference and conduct experiments on several benchmark datasets that demonstrate BiQE significantly outperforms state of the art baselines.
DC.Formatapplication/pdf
DC.Identifier16630
DC.Identifier.pageNumber4968-4977
DC.Identifier.DOI10.1609/aaai.v35i6.16630
DC.Identifier.URIhttps://ojs.aaai.org/index.php/AAAI/article/view/16630
DC.Languageen
DC.RightsCopyright (c) 2021 Association for the Advancement of Artificial Intelligence
DC.SourceProceedings of the AAAI Conference on Artificial Intelligence
DC.Source.ISSN2374-3468
DC.Source.Issue6
DC.Source.Volume35
DC.Source.URIhttps://ojs.aaai.org/index.php/AAAI
DC.SubjectRelational Learning
DC.TitleAnswering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders
DC.TypeText.Serial.Journal
DC.Type.articleTypeAAAI Technical Track Focus Area on Neuro-Symbolic AI
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citation_journal_titleProceedings of the AAAI Conference on Artificial Intelligence
citation_journal_abbrevAAAI
citation_issn2374-3468
citation_authorMathias Niepert
citation_author_institutionNEC Laboratories Europe
citation_titleAnswering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders
citation_languageen
citation_date2021/05/18
citation_volume35
citation_issue6
citation_firstpage4968
citation_lastpage4977
citation_doi10.1609/aaai.v35i6.16630
citation_abstract_html_urlhttps://ojs.aaai.org/index.php/AAAI/article/view/16630
citation_keywordsRelational Learning
citation_pdf_urlhttps://ojs.aaai.org/index.php/AAAI/article/download/16630/16437

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