Title An Automatic Method for Constructing Domain-Specific Ontology Resources
Author(s) Melania Degeratu, Vasileios Hatzivassiloglou

Department of Computer Science, Columbia University, 1214 Amsterdan Avenue, New York, NY 10027, USA

Session P24-T
Abstract Data flow across multiple independent applications and further natural language analysis both require the establishment of a common foundation of terms and relations. Such a foundation can provide in-depth understanding of term equivalence within a domain sublanguage, and serve as a model of concept relations and dependencies. In this paper we discuss a domain-independent, corpus-based method for dictionary-less automatic extraction of ontological knowledge from domain-specific unannotated documents. We present the architecture, algorithms, and results for OntoStruct - a system that uses machine learning and statistical techniques to analyze text sources, discover terms, link equivalent terms into concepts, and learn both hierarchical and non-hierarchical conceptual relations. We report on OntoStruct's results in constructing domain-specific ontological resources and empirical evaluation of their quality.
Keyword(s) Ontologies, ontology construction, automatic learning, ontology evaluation
Language(s) English
Full Paper 705.pdf