SANSA-ML is the Machine Learning (ML) library in the SANSA stack (see http://sansa-stack.net). Algorithms in this repository perform various machine learning tasks directly on RDF/OWL input data. While most machine learning algorithms are based on processing simple features, the machine learning algorithms in SANSA-ML exploit the graph structure and semantics of the background knowledge specified using the RDF and OWL standards. In many cases, this allows to obtain either more accurate or more human-understandable results. In contrast to most other algorithms supporting background knowledge, they scale horizontally using Apache Spark.
The ML layer currently supports the following algorithms:
- RDF graph clustering
- Rule mining in RDF graphs based on AMIE+
Usage example for clusting:
RDFByModularityClustering(sparkSession.sparkContext, numIterations, input, output)Please see https://github.com/SANSA-Stack/SANSA-Examples/tree/master/sansa-examples-spark/src/main/scala/net/sansa_stack/examples/spark/ml for further examples.
Several further algorithms are in development. Please create a pull request and/or contact Jens Lehmann if you are interested in contributing algorithms to SANSA-ML.
Support for Apache Flink is planned in future releases.