DocumentCode :
255967
Title :
Heavy weight ontology learning using text documents
Author :
Kumar, V. ; Chaudhary, S.
Author_Institution :
ABES Eng. Coll., Ghaziabad, India
fYear :
2014
fDate :
11-13 Dec. 2014
Firstpage :
110
Lastpage :
114
Abstract :
Ontology plays an important role not only for data processing in knowledge based systems but also, provide interoperability in heterogeneous environment and is a cornerstone of semantic web technology. The required technology is used for knowledge representation in OWL/RDF format and facilitate faster access of concepts in domain of interest. Development of ontology is a tedious job and requires a lot of man power in terms of experts´ time and knowledge. Although there are various tools and techniques for light weight ontology learning; yet full automation of heavy weight ontology learning from text documents is a distant dream. In this paper we have proposed a framework for learning heavy weight ontology, using text documents written in English language. Initial experimental results are shown for demonstration of our on going research.
Keywords :
learning (artificial intelligence); ontologies (artificial intelligence); text analysis; English language; heavy weight ontology learning; text documents; Agriculture; Educational institutions; Grid computing; Knowledge based systems; Mobile handsets; Ontologies; Semantics; Android application; Knowledge base; Ontology learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel, Distributed and Grid Computing (PDGC), 2014 International Conference on
Conference_Location :
Solan
Print_ISBN :
978-1-4799-7682-9
Type :
conf
DOI :
10.1109/PDGC.2014.7030725
Filename :
7030725
Link To Document :
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