Scaling R-GCN Training with Graph Summarization-Reference-Cited by-同舟云学术

Scaling R-GCN Training with Graph Summarization

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Companion Proceedings of the Web Conference 2022
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Author:

Generale Alessandro¹,Blume Till²,Cochez Michael³

Affiliation:

1. Vrije Universiteit Amsterdam, Netherlands

2. Ernst & Young GmbH WPG - R&D, Germany

3. Vrije Universiteit Amsterdam, Netherlands and Elsevier Discovery Lab, Netherlands

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3487553.3524719

Reference33 articles.

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3. Peter Bloem , Xander Wilcke , Lucas van Berkel , and Victor de Boer . 2021. kgbench: A Collection of Knowledge Graph Datasets for Evaluating Relational and Multimodal Machine Learning . In The Semantic Web, Ruben Verborgh, Katja Hose, Heiko Paulheim, Pierre-Antoine Champin, Maria Maleshkova, Oscar Corcho, Petar Ristoski, and Mehwish Alam (Eds.). Springer International Publishing , Cham , 614–630. https://openreview.net/forum?id=yeK_9wxRDbA Peter Bloem, Xander Wilcke, Lucas van Berkel, and Victor de Boer. 2021. kgbench: A Collection of Knowledge Graph Datasets for Evaluating Relational and Multimodal Machine Learning. In The Semantic Web, Ruben Verborgh, Katja Hose, Heiko Paulheim, Pierre-Antoine Champin, Maria Maleshkova, Oscar Corcho, Petar Ristoski, and Mehwish Alam (Eds.). Springer International Publishing, Cham, 614–630. https://openreview.net/forum?id=yeK_9wxRDbA

4. Incremental and Parallel Computation of Structural Graph Summaries for Evolving Graphs

5. FLUID: A common model for semantic structural graph summaries based on equivalence relations

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