Knowledge graph embeddings: link prediction and beyond

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Notes: Mannheim, Universität Mannheim, Dissertation, 2023

Keyword: Wissensrepräsentation
Maschinelles Lernen
Wissensextraktion
Linked Data

Event: Veröffentlichung

(where): Mannheim

(who): Universitätsbibliothek Mannheim

(when): 2023

Creator: Daniel, Ruffinelli

Contributor: Gemulla, Rainer

URN: urn:nbn:de:bsz:180-madoc-660210

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:29 AM CEST

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Daniel, Ruffinelli
Gemulla, Rainer
Universitätsbibliothek Mannheim

Time of origin

2023

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Knowledge graph embeddings: link prediction and beyond

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Other Objects (12)

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RDF2Vec Light – a lightweight approach for knowledge graph embeddings

Can we predict new facts with open knowledge graph embeddings? A benchmark for open link prediction

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Leveraging literals for knowledge graph embeddings

KGvec2go – Knowledge graph embeddings as a service

Knowledge graph embeddings: open challenges and opportunities

Representation and curation of knowledge graphs with embeddings

Towards binarization of knowledge graph embeddings for node classification

Towards leveraging explicit negative statements in knowledge graph embeddings

Regularized online tensor factorization for sparse knowledge graph embeddings

RDF2Vec Light – a lightweight approach for knowledge graph embeddings

Can we predict new facts with open knowledge graph embeddings? A benchmark for open link prediction

A closer look at sum-based embeddings for knowledge graphs containing procedural knowledge

Knowledge Graph Embeddings for ICU readmission prediction

Multi-domain knowledge graph embeddings for gene-disease association prediction

Leveraging literals for knowledge graph embeddings

KGvec2go – Knowledge graph embeddings as a service

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Representation and curation of knowledge graphs with embeddings

Towards binarization of knowledge graph embeddings for node classification

Towards leveraging explicit negative statements in knowledge graph embeddings

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RDF2Vec Light – a lightweight approach for knowledge graph embeddings

Can we predict new facts with open knowledge graph embeddings? A benchmark for open link prediction

A closer look at sum-based embeddings for knowledge graphs containing procedural knowledge

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