Automatic Learning of Ontologies for the Semantic Web: experiment lexical learning

Abstract

This paper proposes the design of a System for Automatic Learning of Ontologies and Lexical Information (SALOX) for the Dynamic Semantic Ontological Framework for the Semantic Web (DSOFSW). DSOFSW interprets query in natural language (Spanish) to the web, and is composed by five parts; a linguistic ontology for the grammar of Spanish, a lexicon for the lexical information, a database of facts about the system experiences, a task ontology for the linguistic analysis process, and an interpretative ontology of the context. SALOX integrates several methods, approaches and techniques for information extraction, discovery and actualization (pragmatic (user profile, context knowledge), lexical and semantic linguistic information, etc.) in order to update the knowledge used for DSOFSW. SALOX has a component to map the sources of learning with the learning methods, and another to update the linguistic ontology and the lexicon of the DSOFSW. Specifically, in this paper we present the design of the learning unit of lexical information. Keywords: Natural language processing, ontological semantic, machine learning, ontological leaning, semantic web.