DocumentCode
124146
Title
An Approach for Learning and Construction of Expressive Ontology from Text in Natural Language
Author
Ribeiro de Azevedo, Ryan ; Freitas, Fred ; Rocha, Rodrigo G. C. ; Alves de Menezes, Jose Antonio ; de Oliveira Rodrigues, Cleyton Mario ; Silva, Gabriel De F. P. E.
Author_Institution
Comput. Sci., UAG/Fed. Rural Univ. of Pernambuco, Garanhuns, Brazil
Volume
1
fYear
2014
fDate
11-14 Aug. 2014
Firstpage
149
Lastpage
156
Abstract
In this paper, we present an approach based on Ontology Learning and Natural Language Processing for automatic construction of expressive Ontologies, specifically in OWL DL with ALC expressivity, from a natural language text. The viability of our approach is demonstrated through the generation of descriptions of complex axioms from concepts defined by users and glossaries found at Wikipedia. We evaluated our approach in an experiment with entry sentences enriched with hierarchy axioms, disjunction, conjunction, negation, as well as existential and universal quantification to impose restriction of properties. The obtained results prove that our model is an effective solution for knowledge representation and automatic construction of expressive Ontologies. Thereby, it assists professionals involved in processes for obtain, construct and model knowledge domain.
Keywords
learning (artificial intelligence); natural language processing; ontologies (artificial intelligence); text analysis; ALC expressivity; OWL DL; Wikipedia; complex axioms descriptions; conjunction; disjunction; entry sentences; existential quantification; expressive ontology; glossaries; hierarchy axioms; knowledge domain; knowledge representation; natural language processing; natural language text; negation; ontology learning; universal quantification; Cognition; OWL; Ontologies; Semantics; Syntactics; Tin; Vehicles; Descriprion Logic; Knowledge Representation; Natural Language Processing; Ontology; Ontology Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on
Conference_Location
Warsaw
Type
conf
DOI
10.1109/WI-IAT.2014.28
Filename
6927537
Link To Document