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Abstract. Web 2.0 is turning current Web into social platform for knowing people and sharing information. The Web is strongly socially linked than ever. This paper takes major social tagging systems as examples, namely delicious, flickr and youtube, to analyze the social phenomena in the Social Web in order to identify the way of mediating and linking social data. A simple Upper Tag Ontology (UTO) is proposed to integrate different social tagging data and mediate and link with other related social metadata.

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This paper presents the semi-automatic construction method of a practical ontology by using various resources. In order to acquire a reasonably practical ontology in a limited time and with less manpower, we extend the Kadokawa thesaurus by inserting additional semantic relations into its hierarchy, which are classified as case relations and other semantic relations. The former can be obtained by converting valency information and case frames from previously-built computational dictionaries used in machine translation. The latter can be acquired from concept co-occurrence information, which is extracted automatically from large corpora. The ontology stores rich semantic constraints among 1,110 concepts, and enables a natural language processing system to resolve semantic ambiguities by making inferences with the concept network of the ontology. In our practical machine translation system, our ontology-based word sense disambiguation method achieved an 8.7% improvement over methods which do not use an ontology for Korean translation.