Graph Machine Learning Dataset SOA-SW

<p><strong>SOA-SW</strong> &nbsp;is a heterogeneous graph machine learning dataset based on the RDF knowledge graph <a href="doi.org/10.5281/zenodo.10299132">SemOpenAlex-SemanticWeb</a>.</p><p>SOA-SW contains six node types - works (95,575 nodes), authors (19,970 nodes), concepts (38,050 nodes), sources (10,739 nodes), institutions (5,846 nodes), and publishers (786 nodes), and seven edge types. &nbsp;</p><p>Each node has rich semantic node features as node representation (content-based and topology-based node features are available).</p><p>More information can be found in the README.txt and on <a href="https://github.com/davidlamprecht/AutoRDF2GML">https://github.com/davidlamprecht/AutoRDF2GML.</a></p><p>&nbsp;</p><p><strong>soa-sw-homogeneous-author</strong> only models the co-author network of SOA-SW.</p><p>It is a homogeneous graph containing the author node type (19,970 nodes) and the edge type author- author.</p><p>The authors' content-based features (nodes-nld) are based on the titles and abstracts of the authors' works (128-dimensional SciBERT embeddings).</p>