Documenting Knowledge Graph Embedding and Link Prediction using Knowledge Graphs

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource, 68 S.

Language: Englisch

Event: Veröffentlichung

(where): Hannover

(who): Gottfried Wilhelm Leibniz Universität Hannover

(when): 2024

Event: Veröffentlichung

(where): Hannover

(who): Technische Informationsbibliothek (TIB)

(when): 2024

Creator: Zhao, Huaxia

DOI: 10.15488/16093

URN: urn:nbn:de:101:1-2024021501105442266024

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:37 AM CEST

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Associated

Zhao, Huaxia
Gottfried Wilhelm Leibniz Universität Hannover
Technische Informationsbibliothek (TIB)

Time of origin

2024

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Multiple Objective Learning for Effective Knowledge Graph Embedding

Knowledge graph embedding methods for entity alignment: experimental review

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Knowledge graph embedding for data mining vs. knowledge graph embedding for link prediction – two sides of the same coin?

Temporal Knowledge Graph Embedding and Reasoning

Relation path embedding in knowledge graphs

Knowledge graph embedding closed under composition

Prediction of adverse drug reactions based on knowledge graph embedding

Knowledge Graph Embedding via Triplet Component Interactions

A survey: knowledge graph entity alignment research based on graph embedding

Multiple Objective Learning for Effective Knowledge Graph Embedding

Knowledge graph embedding methods for entity alignment: experimental review

Universal preprocessing operators for embedding knowledge graphs with literals

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Documenting Knowledge Graph Embedding and Link Prediction using Knowledge Graphs

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Other Objects (12)

Documenting Data Integration Using Knowledge Graphs

Embedding Based Link Prediction for Knowledge Graph Completion

Knowledge graph embedding for data mining vs. knowledge graph embedding for link prediction – two sides of the same coin?

Temporal Knowledge Graph Embedding and Reasoning

Relation path embedding in knowledge graphs

Knowledge graph embedding closed under composition

Prediction of adverse drug reactions based on knowledge graph embedding

Knowledge Graph Embedding via Triplet Component Interactions

A survey: knowledge graph entity alignment research based on graph embedding

Multiple Objective Learning for Effective Knowledge Graph Embedding

Knowledge graph embedding methods for entity alignment: experimental review

Universal preprocessing operators for embedding knowledge graphs with literals

Documenting Data Integration Using Knowledge Graphs

Embedding Based Link Prediction for Knowledge Graph Completion

Knowledge graph embedding for data mining vs. knowledge graph embedding for link prediction – two sides of the same coin?

Temporal Knowledge Graph Embedding and Reasoning

Relation path embedding in knowledge graphs

Knowledge graph embedding closed under composition

Prediction of adverse drug reactions based on knowledge graph embedding

Knowledge Graph Embedding via Triplet Component Interactions

A survey: knowledge graph entity alignment research based on graph embedding

Multiple Objective Learning for Effective Knowledge Graph Embedding

Knowledge graph embedding methods for entity alignment: experimental review

Universal preprocessing operators for embedding knowledge graphs with literals

Documenting Data Integration Using Knowledge Graphs

Embedding Based Link Prediction for Knowledge Graph Completion

Knowledge graph embedding for data mining vs. knowledge graph embedding for link prediction – two sides of the same coin?

Temporal Knowledge Graph Embedding and Reasoning

Relation path embedding in knowledge graphs

Knowledge graph embedding closed under composition

Prediction of adverse drug reactions based on knowledge graph embedding

Knowledge Graph Embedding via Triplet Component Interactions

A survey: knowledge graph entity alignment research based on graph embedding

Multiple Objective Learning for Effective Knowledge Graph Embedding

Knowledge graph embedding methods for entity alignment: experimental review

Universal preprocessing operators for embedding knowledge graphs with literals

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