Today, we released DL-Learner Build 2009-05-06. DL-Learner is a tool for learning OWL class expressions from examples and background knowledge. It extends Inductive Logic Programming (ILP) to Description Logics and the Semantic Web. Some notable features in this release are:
- a new learning algorithm (CELOE) designed specifically for extending OWL ontologies
- a Protege plugin using CELOE
- a manual for getting started using DL-Learner
- performance improvements through stochastic methods
- more learning examples, unit tests, code quality improvements
DL-Learner can be used to:
- solve general supervised Machine Learning problems using ontologies as background knowledge (given as OWL files, SPARQL endpoints, etc.), e.g. it was used to predict whether chemicals can cause cancer
- help knowledge engineers by learning definitions and subclass axioms (see the Protege plugin and another one for OntoWiki is in progress)
- generating user recommendations when browsing knowledge bases
I’d like to thank all contributors, in particular active developers and everyone who sent us valuable feedback.
