An Unsupervised Method for Ontology Population from Textual Sources on the Web

Authors

Fábio Lima, Universidade Federal da Bahia - UFBAFollow
Hilário Tomaz Alves de Oliveira, Universidade Federal de Pernambuco - UFPEFollow
Laís do Nascimento Salvador, Universidade Federal da Bahia - UFBAFollow

Document Type

Article

Publication Date

5-2015

Keywords

Ontologies, Ontology Population, Information Extraction

Abstract

The increasing in the production and availability of unstructured information on the Web grows daily. This abundance of unstructured information is a great challenge for acquisition of structured knowledge. Many approaches have been proposed for extracting information from texts written in natural language. However, only a few studies have investigated the extraction of information from texts written in Portuguese. Thus, this work aims to propose and evaluate an unsupervised method for ontology population using the Web as a big source of information in the context of the Portuguese language. The results of the experiments are encouraging and demonstrated that the proposed approach reached a precision rate of 67% in the instances of ontological classes extraction.

Comments

This paper is in Portuguese (Um Método Não Supervisionado para o Povoamento de Ontologias a partir de Fontes Textuais na Web)

Recommended Citation

Lima, Fábio; de Oliveira, Hilário Tomaz Alves; and Salvador, Laís do Nascimento, "An Unsupervised Method for Ontology Population from Textual Sources on the Web" (2015). Proceedings of the XI Brazilian Symposium on Information Systems (SBSI 2015). 50.
https://aisel.aisnet.org/sbis2015/50