Extracting Ontology from Different Sources

Abstract

Ontologies have become a popular research topic and have been investigated by several artificial intelligence research communities, including knowledge engineering and management, natural language processing and knowledge representation. Ontologies meet a major demand in these fields: they establish shared and common understanding of a domain to facilitate communication among different software applications and users.

Ontology construction, in large, complex application domains, can be lengthy, costly and controversial. Most of existing ontologies construction tools support construction of ontological relations (e.g. taxonomy, equivalence, etc.) but they do not support construction of domain relations, non-taxonomic conceptual relationships, (e.g. causes, caused by, has-member, contain, etc.). The aim of this thesis is to investigate the automation of the ontology building process from structured and unstructured sources. This thesis also aims at proposing approaches related to merging, integrating and maintaining extracted or existing domain ontologies.