Automated Ontology Selection Based on Description Logic
Xiaodong Wang, Lei Guo, Jun Fang · 2008
With the widespread use of Ontology and extension of Ontology repositories, there come deficiencies on Ontology Selection. The deficiencies are mainly low automated level and absence of Ontological knowledge in the selection criteria. To fill the gaps, we propose a Description Logic based Automated Ontology Selection Framework (DL-AOSF), which consists of automated components and is designed to be suitable for various application scenarios. The core algorithm of DL-AOSF adopts dual criteria, viz. topic coverage and knowledge richness, to comprehensively assess the satisfaction of candidates with concrete application information need. Distinguishing from other Ontology selections, DL- AOSF implements the knowledge richness criteria on semantic level, by using knowledge-driven Ontology modularization technique and DL reasoning. The preliminary experimental results indicate DL-AOSF is valid and promising.