DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released
Dear all, The Smart Data Analytics group [1] and the E.T.-db-MOLE sub-group located at the InfAI Leipzig [2] is happy to announce DL-Learner 1.4. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. DL-Learner can … Continue reading → ...
Article accepted in Journal of Web Semantics
We are happy to announce that the article “DL-Learner – A Framework for Inductive Learning on the Semantic Web” by Lorenz Bühmann, Jens Lehmann and Patrick Westphal was accepted for publication in the Journal of Web Semantics: Science, Services and Agents on … Continue reading → ...
DL-Learner 1.2 (Supervised Structured Machine Learning Framework) Released
Dear all, we are happy to announce DL-Learner 1.2. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. DL-Learner can use various RDF and OWL serialization formats as well as SPARQL endpoints as input, can … Continue reading → ...
DL-Learner 1.1 (Supervised Structured Machine Learning Framework) Released
Dear all, we are happy to announce DL-Learner 1.1. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. DL-Learner can use various RDF and OWL serialization formats as well as SPARQL endpoints as input, can … Continue reading → ...
DL-Learner 1.0 (Supervised Structured Machine Learning Framework) Released
Dear all, we are happy to announce DL-Learner 1.0. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. DL-Learner can use various RDF and OWL serialization formats as well as SPARQL endpoints as input, can … Continue reading → ...
