'Ontolearn---A Framework for Large-scale OWL Class Expression Learning in Python', by Caglar Demir et al.
http://jmlr.org/papers/v26/24-1113.html
#owl #ontolearn #sparql
'Ontolearn---A Framework for Large-scale OWL Class Expression Learning in Python', by Caglar Demir et al.
http://jmlr.org/papers/v26/24-1113.html
#owl #ontolearn #sparql
We are delighted that our paper "ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling" by N'Dah Jean Kouagou, Stefan Heindorf, Caglar Demir & Axel Ngonga has been accepted at #IJCAI2024 #MainTrack.๐คฉ๐ฅณ
๐ In ROCES, we introduce a generalization of the classical class expression learning problem. We also propose a learning algorithm for synthesis-based approaches to solve the generalized learning problem.
๐ Exciting news! ๐
Ontolearn 0.7.0 is now released! This update brings some amazing features:
๐ Drill, Tree-based DL Learner (tDL), and CLIP now available!
๐ Introducing the Triple Store Knowledge Base for SPARQL endpoint queries.
๐ Changes to the KnowledgeBase class for triple retrieval and more convenience.
Upgrade now with pip install -U ontolearn and explore the latest enhancements! Check out the release notes here https://github.com/dice-group/Ontolearn/releases/tag/0.7.0