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Reseach Article

Semantic Information Retrieval: An Ontology and RDF-based Model

by S. Mahaboob Hussain, Prathyusha Kanakam, D. Suryanarayana, Swathi Gunnam, Sharmela S.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 156 - Number 9
Year of Publication: 2016
Authors: S. Mahaboob Hussain, Prathyusha Kanakam, D. Suryanarayana, Swathi Gunnam, Sharmela S.
10.5120/ijca2016912575

S. Mahaboob Hussain, Prathyusha Kanakam, D. Suryanarayana, Swathi Gunnam, Sharmela S. . Semantic Information Retrieval: An Ontology and RDF-based Model. International Journal of Computer Applications. 156, 9 ( Dec 2016), 34-38. DOI=10.5120/ijca2016912575

@article{ 10.5120/ijca2016912575,
author = { S. Mahaboob Hussain, Prathyusha Kanakam, D. Suryanarayana, Swathi Gunnam, Sharmela S. },
title = { Semantic Information Retrieval: An Ontology and RDF-based Model },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2016 },
volume = { 156 },
number = { 9 },
month = { Dec },
year = { 2016 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume156/number9/26740-2016912575/ },
doi = { 10.5120/ijca2016912575 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:11.401104+05:30
%A S. Mahaboob Hussain
%A Prathyusha Kanakam
%A D. Suryanarayana
%A Swathi Gunnam
%A Sharmela S.
%T Semantic Information Retrieval: An Ontology and RDF-based Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 156
%N 9
%P 34-38
%D 2016
%I Foundation of Computer Science (FCS), NY, 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
  1. Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Sci Am. 284, 34-43 (2001).
  2. Dai, W., You, Y., Wang, W., Sun, Y., Li, T.: Search Engine System Based on Ontology of Technological Resources. JSW. 6, (2011)
  3. Marzano, G.: Using Resource Description Framework (RDF) for Description and Modeling Place Identity. Procedia Computer Science. 77, 135-140 (2015)
  4. Kim, K., Moon, B., Kim, H.: R3F: RDF triple filtering method for efficient SPARQL query processing. World Wide Web. 18, 317-357 (2013)
  5. Jeon, M., Hong, J., Park, Y.: SPARQL Query Processing System over Scalable Triple Data using SparkSQL Framework. Journal of KIISE. 43, 450-459 (2016)
  6. Segaran, T., Evans, C., Taylor, J.: Programming the Semantic Web. O'Reilly, Beijing (2009)
  7. Suryanarayana, D., et al. "Stepping towards a semantic Web search engine for accurate outcomes in favour of user queries: Using RDF and ontology technologies." 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2015.
  8. Hussain, S. Mahaboob, et al. "Palazzo Matrix Model: An approach to simulate the efficient semantic results in search engines." Electrical, Computer and Communication Technologies (ICECCT), 2015 IEEE International Conference on. IEEE, 2015.
  9. Suryanarayana, D., et al. "Cognitive Analytic Task Based on Search Query Logs for Semantic Identification" IJCTA, 9(21), pp. 273-280, 2016.
Index Terms

Computer Science
Information Sciences

Keywords

RDF SPARQL Semantic Web Semantic Search Information Retrieval