In order to optimize ontology reasoning, a novel boundary-based modular extraction method is introduced for ontologies in EL^＋＋ description logics. The proposed module extraction method is capable of identifying rel...In order to optimize ontology reasoning, a novel boundary-based modular extraction method is introduced for ontologies in EL^＋＋ description logics. The proposed module extraction method is capable of identifying relevant axioms in an ontology based on the notion of boundaries of symbols, with respect to a given reasoning task. Exactness of the method is ensured by discovering all axioms in the original ontology that may be directly or indirectly relevant to boundaries of symbols used in the reasoning task. Compactness of the method is ensured by boundary partition and intersection operation performed in the process of module extraction. The theoretical foundation and a practical algorithm for computing the proposed axiom-based modules are presented. The proposed algorithm is implemented for the description logic EL^＋＋. Experimental results on realworld ontologies show that, based on the proposed modularization method, the performance of ontology reasoning can be significantly improved.展开更多
基金The PhD Programs Foundation of Ministry of Education of China(No20096102120037)
文摘In order to optimize ontology reasoning, a novel boundary-based modular extraction method is introduced for ontologies in EL^＋＋ description logics. The proposed module extraction method is capable of identifying relevant axioms in an ontology based on the notion of boundaries of symbols, with respect to a given reasoning task. Exactness of the method is ensured by discovering all axioms in the original ontology that may be directly or indirectly relevant to boundaries of symbols used in the reasoning task. Compactness of the method is ensured by boundary partition and intersection operation performed in the process of module extraction. The theoretical foundation and a practical algorithm for computing the proposed axiom-based modules are presented. The proposed algorithm is implemented for the description logic EL^＋＋. Experimental results on realworld ontologies show that, based on the proposed modularization method, the performance of ontology reasoning can be significantly improved.
