Context-based term identification and extraction for ontology construction

Abstract

Ontology construction often requires a domain specific corpus in conceptualizing the domain knowledge; specifically, it is an association of terms, relation between terms and related instances. It is a vital task to identify a list of significant term for constructing a practical ontology. In this paper, we present the use of a context-based term identification and extraction methodology for ontology construction from text document. The methodology is using a taxonomy and Wikipedia to support automatic term identification and extraction from structured documents with an assumption of candidate terms for a topic are often associated with its topic-specific keywords. A hierarchical relationship of super-topics and sub-topics is defined by a taxonomy, meanwhile, Wikipedia is used to provide context and background knowledge for topics that defined in the taxonomy to guide the term identification and extraction. The experimental results have shown the context-based term identification and extraction methodology is viable in defining topic concepts and its sub-concepts for constructing ontology. The experimental results have also proven its viability to be applied in a small corpus / text size environment in supporting ontology construction.