DocumentCode :
3303733
Title :
Intelligent semantic question answering system
Author :
Najmi, Erfan ; Hashmi, Khayyam ; Khazalah, Fayez ; Malik, Zaki
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
fYear :
2013
fDate :
13-15 June 2013
Firstpage :
255
Lastpage :
260
Abstract :
The volume of information available on the World Wide Web and the rate of its growth requires new techniques to handle and organize this data. Ontologies are becoming the pivotal methodology to represent domain-specific conceptual knowledge and hence help in providing solutions for Question Answering (QA) systems. This paper introduces an approach for enhancing the capabilities of QA systems using semantic technologies. We implemented an approach to convert the natural language user queries to Resource Description Framework (RDF) triples and find relevant answers. The experiment results show that the proposed technique works very well for single word answers. We believe that with some modifications this approach can be expanded to a wider scale.
Keywords :
natural language processing; ontologies (artificial intelligence); question answering (information retrieval); RDF triples; World Wide Web; domain specific conceptual knowledge; intelligent semantic question answering system; natural language user queries; ontologies; resource description framework; semantic technologies; Google; Natural languages; Ontologies; Organizations; Resource description framework; Search engines; Semantics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetics (CYBCONF), 2013 IEEE International Conference on
Conference_Location :
Lausanne
Type :
conf
DOI :
10.1109/CYBConf.2013.6617431
Filename :
6617431
Link To Document :
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