AutoRDF2GML: Facilitating RDF Integration in Graph Machine Learning
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Beitragende
Abstract
In this paper, we introduce AutoRDF2GML, a framework designed to convert RDF data into data representations tailored for graph machine learning tasks. AutoRDF2GML enables, for the first time, the creation of both content-based features—i.e., features based on RDF datatype properties—and topology-based features—i.e., features based on RDF object properties. Characterized by automated feature extraction, AutoRDF2GML makes it possible even for users less familiar with RDF and SPARQL to generate data representations ready for graph machine learning tasks, such as link prediction, node classification, and graph classification. Furthermore, we present four new benchmark datasets for graph machine learning, created from large RDF knowledge graphs using our framework. These datasets serve as valuable resources for evaluating graph machine learning approaches, such as graph neural networks. Overall, our framework effectively bridges the gap between the Graph Machine Learning and Semantic Web communities, paving the way for RDF-based machine learning applications.
Details
Originalsprache | Englisch |
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Titel | The Semantic Web – ISWC 2024 - 23rd International Semantic Web Conference, Proceedings |
Redakteure/-innen | Gianluca Demartini, Katja Hose, Maribel Acosta, Matteo Palmonari, Gong Cheng, Hala Skaf-Molli, Nicolas Ferranti, Daniel Hernández, Aidan Hogan |
Herausgeber (Verlag) | Springer Science and Business Media B.V. |
Seiten | 115-133 |
Seitenumfang | 19 |
ISBN (Print) | 9783031778469 |
Publikationsstatus | Veröffentlicht - 27 Nov. 2024 |
Peer-Review-Status | Ja |
Publikationsreihe
Reihe | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Band | 15233 LNCS |
ISSN | 0302-9743 |
Konferenz
Titel | 23rd International Semantic Web Conference |
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Kurztitel | ISWC 2024 |
Veranstaltungsnummer | 23 |
Dauer | 11 - 15 November 2024 |
Webseite | |
Ort | Live! Casino & Hotel Maryland |
Stadt | Baltimore |
Land | USA/Vereinigte Staaten |