Title :
Mining of EL-GCIs
Author :
Borchmann, D. ; Distel, F.
Author_Institution :
Fac. of Comput. Sci., Tech. Univ. Dresden, Dresden, Germany
Abstract :
We consider an existing approach for mining general inclusion axioms written in a lightweight Description Logic. In comparison to classical association rule mining, this approach allows more complex patterns to be obtained. Ours is the first implementation of these algorithms for learning Description Logic axioms. We use our implementation for a case study on two real world datasets. We discuss the outcome and examine what further research will be needed for this approach to be applied in a practical setting.
Keywords :
data mining; formal logic; EL-GCI mining; association rule mining; description logic axiom learning algorithm; general inclusion axioms mining; lightweight description logic; Algorithm design and analysis; Association rules; Data models; Drugs; Proteins; Resource description framework; Description Logics; General Inclusion Axioms;
Conference_Titel :
Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4673-0005-6
DOI :
10.1109/ICDMW.2011.119
