이산 Cuckoo Search를 이용한 온톨로지 정렬
Ontology Alignment by Using Discrete Cuckoo Search
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초록
온톨로지 정렬의 목적은 지식을 공유 및 재사용 하는 데 있다. 기존 온톨로지 정렬 시스템은 온톨로지 개념의 모호성 때문에 여러 가지다양한 측정 기법을 사용하고 전수조사를 수행하여 사용자가 만족하는 결과를 얻는다. 온톨로지 개념이 점차 많아짐에 따라 계산이 복잡해지고 걸리는 시간이 기하급수적으로 증가하여 처리 과정에서 오류가 발생한다. 이를 해결하기 위하여 메타 휴리스틱 알고리즘을 사용하는메타 매칭이 연구되고 있다. 기존 메타 매칭 시스템에서는 사용하는 파라미터가 많기 때문에 온톨로지 정렬 처리에 계산이 복잡하고 특정도메인의 다양한 데이터에 따라 조율이 요구되어 온톨로지 정렬 탐색에 좋은 성능을 보여주지 못했다. 이 논문에서는 온톨로지 정렬을 쉽고 간단한 계산을 통해 높은 성능을 목표로 하여 DCS(Discrete Cuckoo Search) 를 사용한 온톨로지 정렬 알고리즘을 제안한다. 제안한 알고리즘은 Levy Flight 분포에 따른 탐색으로 효율적인 전략을 보여준다. 제안된 알고리즘은 OAEI 2012(Ontology Alignment EvaluationInitiative)에서 제공하는 벤치마크 데이터와 제안 알고리즘을 사용하여 성능을 평가한다.
Abstract
Ontology alignment is the way to share and reuse of ontology knowledge. Because of the ambiguity of concept, most ontologyalignment systems combine a set of various measures and complete enumeration to provide the satisfactory result. However, calculatingprocess becomes more complex and required time increases exponentially since the number of concept increases, more errors can appearat the same time. Lately the focus is on meta-matching using the heuristic algorithm. Existing meta-matching system tune extraparameter and it causes complex calculating, as a consequence, the results in the various data of specific domain are not good performed. In this paper, we propose a high performance algorithm by using DCS that can solve ontology alignment through simple process. Itprovides an efficient search strategy according to distribution of Levy Flight. In order to evaluate the approach, benchmark data fromthe OAEI 2012 is employed. Through the comparison of the quality of the alignments which uses DCS with state of the art ontologymatching systems.
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