• Journal of KIISE:Software and Applications
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• v.33 no.1
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• pp.114-129
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• 2006

Ontology mapping is the task of finding semantic correspondences between two ontologies. In order to improve the effectiveness of ontology mapping, we need to consider the characteristics and constraints of data models used for implementing ontologies. Earlier research on ontology mapping, however, has proven to be inefficient because the approach should transform input ontologies into graphs and take into account all the nodes and edges of the graphs, which ended up requiring a great amount of processing time. In this paper, we propose a multi-strategic mapping approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the topic maps. Our multi-strategic mapping approach includes a topic name-based mapping, a topic property-based mapping, a hierarchy-based mapping, and an association-based mapping approach. And it also uses a hybrid method in which a combined similarity is derived from the results of individual mapping approaches. In addition, we don't need to generate a cross-pair of all topics from the ontologies because unmatched pairs of topics can be removed by characteristics and constraints of the topic maps. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Yahoo german literature dictionary as input ontologies. Our experiments show that the automatically generated mapping results conform to the outputs generated manually by domain experts, which is very promising for further work.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.131-136
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• 2007

토픽맵은 RDF에 기반을 둔 OWL과 많은 유사점을 갖지만, 양자는 역사적, 기술적, 의도하는 목적에서 차이가 있다. 토픽맵은 ISO 표준이지만, OWL은 W3C의 온톨로지 개발 표준언어로서 양자는 각각의 제약언어, 데이터 모델, 그리고 일련의 구문들을 별개로 갖는다. 그러나 토픽맵과 OWL 양자는 지식을 표현하는 온톨로지 언어라는 공통적 특성을 가지며, 술어로직에 기반을 두고 있고, XML포맷이기 때문에 상호간에 매핑이 가능하다. 논문의 목적은 토픽맵과 OWL의 메타모델로부터 온톨로지 정보자원의 공유, 교환, 통합에 접근시킨다. 따라서 각각의 메타모델에서 주요 요소를 추출하고, 이들의 의미적인 측면과 구조적인 측면의 요소들의 손실이 발생되지 않도록 매핑을 수행한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.147-150
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• 2007

본 논문에서는 토픽맵 기반의 온톨로지 병합 과정에서 발생할 수 있는 충돌의 유형을 트리 구조로 정의하고 충돌 탐지 및 해결을 통하여 두 온톨로지를 하나로 병합하는 기법을 제안한다. 병합충돌은 의미적 대응 요소들의 유사값에 기반하여 엘리먼트기반, 구조기반 임시기반의 트리 구조로 분류되고 이 충돌 트리를 이용하여 두 매핑 요소사이의 병합충돌을 탐지하고 해결한다. 실험을 위해 토픽맵 질의언어 tolog를 사용하여 동서양 철학온톨로지 및 독일 문학온톨로지들의 병합 전과 후의 질의 결과를 비교하고 이를 정확율과 재현율로 병합 성능을 평가하였으며 그 결과 손실없는 병합이 가능함을 보였다.

• Journal of KIISE:Software and Applications
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• v.33 no.9
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• pp.787-801
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• 2006

Ontology merging describes the process of integrating two ontologies into a new ontology. How this is done best is a subject of ongoing research in the Semantic Web, Data Integration, Knowledge Management System, and other ontology-related application systems. Earlier research on ontology merging, however, has studied for developing effective ontology matching approaches but missed analyzing and solving methods of problems of merging two ontologies given correspondences between them. In this paper, we propose a specific ontology merging process and a generic operator, T-MERGE, for integrating two source ontologies into a new ontology. Also, we define a taxonomy of merging conflicts which is derived from differing representations between input ontologies and a method for detecting and resolving them. Our T-MERGE operator encapsulates the process of detection and resolution of conflicts and merging two entities based on given correspondences between them. We define a data structure, MergeLog, for logging the execution of T-MERGE operator. MergeLog is used to inform detailed results of execution of merging to users or recover errors. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Naver philosophy dictionary as input ontologies. Our experiments show that the automatic merging module compared with manual merging by a expert has advantages in terms of time and effort.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.175-177
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• 2004

In this paper, we provide a mechanism to map topics between similar Topic Map ontologies, which enlarge the capacities of current Topic Maps. That is, there is no explicit way to map topics across multiple Topic Maps in current technology. Therefore, our approach provide semi-automatic or automatic mapping of topics between Topic Maps. In order to map the topics, we provide precise definitions of mapping properties and mapping rules.