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Ontology alignment, or ontology matching, is the process of determining correspondences between concepts. A set of correspondences is also called an alignment. The phrase takes on a slightly different meaning, in computer science, cognitive science or philosophy. ==Computer Science== For computer scientists, concepts are expressed as labels for data. Historically, the need for ontology alignment arose out of the need to integrate heterogeneous databases, ones developed independently and thus each having their own data vocabulary. In the Semantic Web context involving many actors providing their own ontologies, ontology matching has taken a critical place for helping heterogeneous resources to interoperate. Ontology alignment tools find classes of data that are "semantically equivalent," for example, "Truck" and "Lorry." The classes are not necessarily logically identical. According to Euzenat and Shvaiko (2007),〔Jérôme Euzenat and Pavel Shvaiko. 2007. (Ontology matching ), Springer-Verlag, 978-3-540-49611-3.〕 there are three major dimensions for similarity: syntactic, external, and semantic. Coincidentally, they roughly correspond to the dimensions identified by Cognitive Scientists below. A number of tools and frameworks have been developed for aligning ontologies, some with inspiration from Cognitive Science and some independently. Ontology alignment tools have generally been developed to operate on database schemas,〔J. Berlin and A. Motro. 2002. (Database Schema Matching Using Machine Learning with Feature Selection ). Proc. of the 14th International Conference on Advanced Information Systems Engineering, pp. 452-466〕 XML schemas,〔D. Aumueller, H. Do, S. Massmann, E. Rahm. 2005. (Schema and ontology matching with COMA++ ). Proc. of the 2005 International Conference on Management of Data, pp. 906-908〕 taxonomies,〔S. Ponzetto, R. Navigli. 2009. ("Large-Scale Taxonomy Mapping for Restructuring and Integrating Wikipedia" ). Proc. of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), Pasadena, California, pp. 2083-2088.〕 formal languages, entity-relationship models,〔A. H. Doan, A. Y. Halevy. (Semantic integration research in the database community: A brief survey ). AI magazine, 26(1), 2005〕 dictionaries, and other label frameworks. They are usually converted to a graph representation before being matched. Since the emergence of the Semantic Web, such graphs can be represented in the Resource Description Framework line of languages by triples of the form In this context, aligning ontologies is sometimes referred to as "ontology matching". The problem of Ontology Alignment has been tackled recently by trying to compute matching first and mapping (based on the matching) in an automatic fashion. Systems like DSSim, X-SOM〔 〕 or COMA++ obtained at the moment very high precision and recall.〔 The (Ontology Alignment Evaluation Initiative ) aims to evaluate, compare and improve the different approaches. More recently, a technique useful to minimize the effort in mapping validation and visualization has been presented which is based on Minimal Mappings. Minimal mappings are high quality mappings such that i) all the other mappings can be computed from them in time linear in the size of the input graphs, and ii) none of them can be dropped without losing property i). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Ontology alignment」の詳細全文を読む スポンサード リンク
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