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