DL-Learner 1.0 Beta 3

Tool for supervised Machine Learning in OWL and Description Logics
The DL-Learner software learns concepts in Description Logics (DLs) from user-provided examples. Equivalently, it can be used to learn classes in OWL ontologies from selected objects. DL-Learner extends Inductive Logic Programming to Descriptions Logics and the Semantic Web.

The goal of DL-Learner is to provide a DL/OWL based machine learning tool to support knowledge engineers in constructing knowledge and solve supervised learnings tasks and learning about the data they created.

Main features:

  • implements different algorithms:
  • a refinement operator based algorithm
  • a genetic programming algorithm
  • a hybrid algorithm using genetic refinement operators
  • (random learning, brute force learning)
  • supports different kinds of learning problems:
  • learning concept definitions and inclusion axioms
  • learning from positive and negative examples as well as only from positive examples
  • supports different input formats:
  • OWL files
  • N-triple files
  • internal representation in config files
  • SPARQL endpoints
  • different reasoner adapters:
  • DIG interface: allows all major reasoners
  • OWL API interface (alpha): FaCT++, Pellet
  • KAON2: direct Java API access (may be removed in the future, because KAON2 is not open source)
  • different user interfaces:
  • command line
  • web service
  • planned: PHP client
  • planned: Java Swing based GUI
  • easily extensible through a component model
  • 4 types of components: knowledge sources, reasoners, learning problems, learning algorithms
  • to implement a new component of one of the above types you only have to extend the correct class in org.dllearner.core and add the name of your file to the components.ini file
  • allows a wide range of configuration options

last updated on:
May 23rd, 2014, 19:17 GMT
file size:
194.2 MB
developed by:
Jens Lehmann
license type:
operating system(s):
Mac OS X
binary format:
Universal Binary
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What's New in version 20100807
  • support for OWL API 3
  • ORE tool based on DL-Learner algorithms (soon to be migrated to an own project)
  • implemented several new heuristics, e.g. generalised F-Measure
  • stochastic approximation of computing F-Measure
read full changelog

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