DL-Learner_Logo2015_rgb-300x95a tool for supervised Machine Learning in OWL and Description Logics

DL-Learner is a tool for learning concepts in Description Logics (DLs) from user-provided examples. Equivalently, it can be used to learn classes in OWL ontologies from selected objects. The goal of DL-Learner is to support knowledge engineers in constructing knowledge and learning about the data they created.

Project Team


 

Publications


  1. DL-Learner—A framework for inductive learning on the Semantic Web by Lorenz Bühmann, Jens Lehmann, and Patrick Westphal in Web Semantics: Science, Services and Agents on the World Wide Web [BibTex]
  2. Towards SPARQL-Based Induction for Large-Scale RDF Data sets by Simon Bin, Lorenz Bühmann, Jens Lehmann, and Axel-Cyrille Ngonga Ngomo in ECAI 2016 - Proceedings of the 22nd European Conference on Artificial Intelligence (Editors: Gal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, and Frank van Harmelen) [BibTex]
  3. DBpedia - A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia by Jens Lehmann, Robert Isele, Max Jakob, Anja Jentzsch, Dimitris Kontokostas, Pablo N. Mendes, Sebastian Hellmann, Mohamed Morsey, Patrick van Kleef, Sören Auer, and Christian Bizer in Semantic Web Journal [BibTex]
  4. The GeoKnow Generator Workbench: An Integration Platform for Geospatial Data by Alejandra Garcia-Rojas, Daniel Hladky, Matthias Wauer, Robert Isele, Claus Stadler, and Jens Lehmann in Proceedings of the 3rd International Workshop on Semantic Web Enterprise Adoption and Best Practice [BibTex]
  5. An Introduction to Ontology Learning by Jens Lehmann and Johanna Voelker in Perspectives on Ontology Learning (Editors: Jens Lehmann and Johanna Voelker) [BibTex]
  6. Concept Learning by Jens Lehmann, Nicola Fanizzi, Lorenz Bühmann, and Claudia d'Amato in Perspectives on Ontology Learning (Editors: Jens Lehmann and Johanna Voelker) [BibTex]
  7. CROCUS: Cluster-based ontology data cleansing by Didier Cherix, Ricardo Usbeck, Andreas Both, and Jens Lehmann in Proceedings of the 2nd International Workshop on Semantic Web Enterprise Adoption and Best Practice [BibTex]
  8. Databugger: A Test-driven Framework for Debugging the Web of Data by Dimitris Kontokostas, Patrick Westphal, Sören Auer, Sebastian Hellmann, Jens Lehmann, and Roland Cornelissen in Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion [BibTex] 
  9. GeoKnow: Making the Web an Exploratory Place for Geospatial Knowledge by Spiros Athanasiou, Daniel Hladky, Giorgos Giannopoulos, Alejandra Garc'ıa-Rojas, and Jens Lehmann in ERCIM News [BibTex]
  10. Inductive Lexical Learning of Class Expressions by Lorenz Bühmann, Daniel Fleischhacker, Jens Lehmann, Andre Melo, and Johanna Völker in Knowledge Engineering and Knowledge Management (Editors: Krzysztof Janowicz, Stefan Schlobach, Patrick Lambrix, and Eero Hyvönen) [BibTex]
  11. Perspectives On Ontology Learning (Editors: Jens Lehmann and Johanna Voelker) [BibTex]
  12. Supporting the Data Lifecycle at a Global Publisher using the Linked Data Stack by Christian Dirschl, Katja Eck, and Jens Lehmann in ERCIM News [BibTex]
  13. Test-driven Evaluation of Linked Data Quality by Dimitris Kontokostas, Patrick Westphal, Sören Auer, Sebastian Hellmann, Jens Lehmann, Roland Cornelissen, and Amrapali J. Zaveri in Proceedings of the 23rd International Conference on World Wide Web [BibTex] 
  14. Pattern Based Knowledge Base Enrichment by Lorenz Bühmann and Jens Lehmann in The Semantic Web -- ISWC 2013 (Editors: Harith Alani, Lalana Kagal, Achille Fokoue, Paul Groth, Chris Biemann, JosianeXavier Parreira, Lora Aroyo, Natasha Noy, Chris Welty, and Krzysztof Janowicz) [BibTex]
  15. Improving the Performance of a SPARQL Component for Semantic Web Applications by Didier Cherix, Sebastian Hellmann, and Jens Lehmann in JIST [BibTex]
  16. Navigation-induced Knowledge Engineering by Example by Sebastian Hellmann, Jens Lehmann, Jörg Unbehauen, Claus Stadler, Thanh Nghia Lam, and Markus Strohmaier in JIST [BibTex]
  17. Universal OWL Axiom Enrichment for Large Knowledge Bases by Lorenz Bühmann and Jens Lehmann inProceedings of EKAW 2012 [BibTexs]
  18. AutoSPARQL: Let Users Query Your Knowledge Base by Jens Lehmann and Lorenz Bühmann in Proceedings of ESWC 2011 [BibTex]
  19. Class expression learning for ontology engineering by Jens Lehmann, Sören Auer, Lorenz Bühmann, and Sebastian Tramp (geb. Dietzold) in Journal of Web Semantics [BibTex]
  20. Learning of OWL Class Expressions on Very Large Knowledge Bases and its Applications. by Sebastian Hellmann, Jens Lehmann, and Sören Auer in Learning of OWL Class Expressions on Very Large Knowledge Bases and its Applications (Editors: Interoperability Semantic Services and Web Applications: Emerging Concepts) [BibTex]
  21. Towards Integrating Fuzzy Logic Capabilities into an Ontology-based Inductive Logic Programming Framework by Josué Iglesias and Jens Lehmann in Proc. of the 11th International Conference on Intelligent Systems Design and Applications (ISDA) [BibTex]
  22. Concept Learning in Description Logics Using Refinement Operators by Jens Lehmann and Pascal Hitzler inMachine Learning journal [BibTex]
  23. HANNE - A Holistic Application for Navigational Knowledge Engineering by Sebastian Hellmann, Jörg Unbehauen, and Jens Lehmann in Posters and Demos of ISWC 2010 [BibTex]
  24. Learning OWL Class Expressions by Jens Lehmann [BibTex]
    Note: PhD in Computer Science
  25. Learning OWL Class Expressions by Jens Lehmann (Editors: Pascal Hitzler) [BibTex]
    Note: ISBN 978-3-89838-336-3.2010
  26. ORE - A Tool for Repairing and Enriching Knowledge Bases by Jens Lehmann and Lorenz Bühmann inProceedings of the 9th International Semantic Web Conference (ISWC2010) [BibTex]
  27. The TIGER Corpus Navigator by Sebastian Hellmann, Jörg Unbehauen, Christian Chiarcos, and Axel-Cyrille Ngonga Ngomo in Proceedings of the Ninth International Workshop on Treebanks and Linguistic Theories (TLT9) [BibTex]
  28. DL-Learner: Learning Concepts in Description Logics by Jens Lehmann in Journal of Machine Learning Research (JMLR) [BibTex]
  29. Ideal Downward Refinement in the EL Description Logic by Jens Lehmann and Christoph Haase in Inductive Logic Programming, 19th International Conference, ILP 2009, Leuven, Belgium [BibTex]
  30. Learning of OWL Class Descriptions on Very Large Knowledge Bases by Sebastian Hellmann, Jens Lehmann, and Sören Auer in International Journal on Semantic Web and Information Systems [BibTex]
  31. Semantische Mashups auf Basis Vernetzter Daten by Sören Auer, Jens Lehmann, and Chris Bizer in Social Semantic Web (Editors: Andreas Blumauer and Tassilo Pellegrini) [BibTex]
  32. A Refinement Operator Based Learning Algorithm for the $ALC$ Description Logic by Jens Lehmann and Pascal Hitzler in Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007 [BibTex]
    Note: Best Student Paper Award
  33. DBpedia Navigator by Jens Lehmann and Sebastian Knappe in ISWC Semantic Challenge Proceedings[BibTex]
    Note: Semantic Web Challenge, International Semantic Web Conference 2008
  34. Foundations of Refinement Operators for Description Logics by Jens Lehmann and Pascal Hitzler inInductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007(Editors: Hendrik Blockeel, Jan Ramon, Jude W. Shavlik, and Prasad Tadepalli) [BibTex]
    Note: Best Student Paper Award
  35. Learning of OWL Class Descriptions on Very Large Knowledge Bases by Sebastian Hellmann, Jens Lehmann, and Sören Auer in Proceedings of the Poster and Demonstration Session at the 7th International Semantic Web Conference (ISWC2008), Karlsruhe, Germany, October 28, 2008 (Editors: Christian Bizer and Anupam Joshi) [BibTex]
  36. Hybrid Learning of Ontology Classes by Jens Lehmann in Proc. of the 5th Int. Conference on Machine Learning and Data Mining MLDM [BibTex]