- From: Jens Lehmann <lehmann@informatik.uni-leipzig.de>
- Date: Mon, 13 Oct 2008 18:37:09 +0200
- To: semantic-web@w3.org
Hello, today we released DL-Learner Build 2008-10-13. DL-Learner [1] is a tool for learning complex class descriptions from examples and background knowledge. It extends Inductive Logic Programming to Description Logics and the Semantic Web. Downloads are available at [2]. For a list of the most important changes since the previous release (Build 2008-02-18), see the Changelog [3]. Some notable features are: * addition of a new learning algorithm, which uses background knowledge more efficiently to find solutions of learning problems * a GUI as interface to create or modify configuration files and execute algorithms * a fast approximate instance checking algorithm decreasing the time for example coverage checks (the most expensive operation) significantly, thereby improving overall performance * a matured fragment extraction algorithm, which allows to grab OWL-DL fragments from large knowledge bases (using SPARQL) containing enough relevant information to conduct concept learning, while they are small enough to reason efficiently[4] 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 [5] * help knowledge engineers by learning definitions and subclass axioms (plugins for Protege and OntoWiki in progress) * support searching/navigating/recommendations in knowledge bases DL-Learner is developed at the AKSW [6] research group. I'd like to thank all contributors, in particular Sebastian Hellmann, for their support. Kind regards, Jens Lehmann [1] http://dl-learner.org [2] http://sourceforge.net/projects/dl-learner/ [3] http://dl-learner.org/wiki/ChangeLog [4] http://jens-lehmann.org/files/2008_kb_extraction.pdf [5] http://dl-learner.org/wiki/Carcinogenesis [6] http://aksw.org -- Dipl. Inf. Jens Lehmann Department of Computer Science, University of Leipzig Homepage: http://www.jens-lehmann.org GPG Key: http://jens-lehmann.org/jens_lehmann.asc
Received on Monday, 13 October 2008 16:37:39 UTC