The Problem of Learning Non-taxonomic Relationships of Ontologies from Text

Manual construction of ontologies by domain experts and knowledge engineers is a costly task. Thus, automatic and/or semi-automatic approaches to their development are needed. Ontology Learning aims at identifying its constituent elements, such as non-taxonomic relationships, from textual information sources. This article presents a discussion of the problem of Learning Non-Taxonomic Relationships of Onto logics and defines its generic process. Three techniques representing the state of the art of Learning Non-Taxonomic Relationships of Ontologies are described and the solutions they provide are discussed along with their advantages and limitations.