Literal2Feature - An automatic scalable RDF graph feature extractor
International Conference on Semantic Systems (SEMANTICS), Farshad B. Moghaddam, Carsten Felix Draschner, Jens Lehmann and Hajira Jabeen
TL;DR ⏱️
- Scalable RDF graph feature extraction
- Explainable feature matrix
- Integration with the Semantic Analytics Stack
Literal2Feature is a generic, distributed, and scalable software framework for translating massive RDF data into an explainable feature matrix. Many standard ML algorithms can make use of this matrix. Our method uses Semantic Web and Big Data technologies to extract a variety of features from a big RDF graph by deep traversing it. The proposed framework is open-source, technically documented, and wholly integrated into the Semantic Analytics Stack community project.