Using domain specific generated rules for automatic ontology population

Abstract

This article proposes a process for automatic population of ontologies from text that applies natural language processing and information extraction techniques to acquire and classify ontology instances. The work is part of HERMES, an FCT/CAPES research project looking for techniques and tools for automating the process of ontology learning and population. Two experiments using a legal and a tourism corpora were conducted in order to evaluate it. The results indicate that our approach can extract and classify instances with high effectiveness with the additional advantage of domain independence.