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Semantic Information Retrieval: An Ontology and RDF-based Model

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
S. Mahaboob Hussain, Prathyusha Kanakam, D. Suryanarayana, Swathi Gunnam, Sharmela S.
10.5120/ijca2016912575

Mahaboob S Hussain, Prathyusha Kanakam, D Suryanarayana, Swathi Gunnam and Sharmela S.. Semantic Information Retrieval: An Ontology and RDF-based Model. International Journal of Computer Applications 156(9):34-38, December 2016. BibTeX

@article{10.5120/ijca2016912575,
	author = {S. Mahaboob Hussain and Prathyusha Kanakam and D. Suryanarayana and Swathi Gunnam and Sharmela S.},
	title = {Semantic Information Retrieval: An Ontology and RDF-based Model},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {9},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {34-38},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume156/number9/26740-2016912575},
	doi = {10.5120/ijca2016912575},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Retrieving the specific knowledge from the Web becomes a challenging task as it contributes enormous amounts of unorganized textual data. This paper focuses on lessening the time consumed by the user for searching the documents and providing the results as per user intention. This paper demonstrates a semantic query language SPARQL to extract the data from the student career knowledge base constructed using Resource Description Framework (RDF) that gives relevant information to the user. This paper provides the requested information by understanding user’s query intention with the created career ontology using RDF and SPARQL in a semantic manner.

References

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  9. Suryanarayana, D., et al. "Cognitive Analytic Task Based on Search Query Logs for Semantic Identification" IJCTA, 9(21), pp. 273-280, 2016.

Keywords

RDF, SPARQL, Semantic Web, Semantic Search, Information Retrieval