Syntactic and semantic English-Korean Machine Translation using ontology

This paper presents the syntactic and semantic method for English-Korean Machine Translation (MT) using ontology for Web-based MT system. We first build word class ontology from the English corpus and calculate the weight of relation between words in the same or different ontologies by counting the frequency of co-occurrence. With our constructed ontologies, we introduce the MT system model including the syntactic and semantic translation module. Each module translates the source language in different way. The syntactic translation module transforms the structure of English into Korean structure. The semantic translation module extracts an exact meaning of a word using ontologies. Through the both translation modules the source language is naturally translated into a target language.