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Christian Meilicke

University of Mannheim

SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models



Simon Ott , Christian Meilicke , Matthias Samwald


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Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs



Simon Ott , Laura Graf , Asan Agibetov , Christian Meilicke , Matthias Samwald


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Reinforced Anytime Bottom Up Rule Learning for Knowledge Graph Completion



Christian Meilicke , Melisachew Wudage Chekol , Manuel Fink , Heiner Stuckenschmidt


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Do Embedding Models Perform Well for Knowledge Base Completion?



Yanjie Wang , Daniel Ruffinelli , Rainer Gemulla , Samuel Broscheit , Christian Meilicke


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Using Abduction in Markov Logic Networks for Root Cause Analysis



Joerg Schoenfisch , Janno von Stulpnagel , Jens Ortmann , Christian Meilicke , Heiner Stuckenschmidt


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Evaluating Ontology Matching Systems on Large, Multilingual and Real-world Test Cases



Christian Meilicke , Ondrej Sváb-Zamazal , Cássia Trojahn , Ernesto Jiménez-Ruiz , José-Luis Aguirre , Heiner Stuckenschmidt , Bernardo Cuenca Grau

* Technical Report of the OAEI 2011.5 Evaluation Campaign 

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