# Towards an Error-Tolerant Construction of EL^ -Ontologies from Data Using Formal Concept Analysis

In the work of Baader and Distel, a method has been proposed to axiomatize all general concept inclusions (GCIs) expressible in the description logic $mathcal{EL}^{bot}$ and valid in a given interpretation $mathcal{I}$. This provides us with an effective method to learn $mathcal{EL}^{bot}-ontologies from interpretations. In this work, we want to extend this approach in the direction of handling errors, which might be present in the data-set. We shall do so by not only considering valid GCIs but also those whose confidence is above a given threshold$c$. We shall give the necessary definitions and show some first results on the axiomatization of all GCIs with confidence at least$c$. Finally, we shall provide some experimental evidence based on real-world data that supports our approach. • Forschungsgruppe:Research Group: Automatentheorie The final publication is available at Springer. @inproceedings{ Borc-ICFCA13, author = {Daniel {Borchmann}}, booktitle = {Formal Concept Analysis, 11th International Conference, ICFCA 2013, Dresden, Germany, May 21-24, 2013. Proceedings}, editor = {Peggy {Cellier} and Felix {Distel} and Bernhard {Ganter}}, pages = {60--75}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Towards an Error-Tolerant Construction of$\mathcal{EL}^{\bot}\$ -Ontologies from Data Using Formal Concept Analysis},