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Reseach Article

Ontology based Semantic Indexing Approach for Information Retrieval System

by Sajendra Kumar, Ram Kumar Rana, Pawan Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 12
Year of Publication: 2012
Authors: Sajendra Kumar, Ram Kumar Rana, Pawan Singh
10.5120/7678-0978

Sajendra Kumar, Ram Kumar Rana, Pawan Singh . Ontology based Semantic Indexing Approach for Information Retrieval System. International Journal of Computer Applications. 49, 12 ( July 2012), 14-18. DOI=10.5120/7678-0978

@article{ 10.5120/7678-0978,
author = { Sajendra Kumar, Ram Kumar Rana, Pawan Singh },
title = { Ontology based Semantic Indexing Approach for Information Retrieval System },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 12 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number12/7678-0978/ },
doi = { 10.5120/7678-0978 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:46:05.571376+05:30
%A Sajendra Kumar
%A Ram Kumar Rana
%A Pawan Singh
%T Ontology based Semantic Indexing Approach for Information Retrieval System
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 12
%P 14-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper shows how the gap between the texts based web pages and the Resource Descriptive Framework based pages of the semantic web can be bridged by ontologies. Most traditional search engines use indexes that are engineered at the syntactical level and come back hits based mostly on straightforward string comparisons or use the static keyword based indexing. However, the indexes don't contain synonyms, cannot differentiate between homonyms ('mouse' as a Pointing device vs. 'Mouse' as a living animal) and users receive completely different search results after they use different conjugation varieties of identical word. During this work, we have a tendency to gift a system that uses ontologies and Natural Language Processing techniques to construct index, and therefore supports word sense disambiguation. Therefore the retrieval of document that contains equivalent term as the context demands is achieved to provide efficient search engines through ontological indexing.

References
  1. Clarck C. , Cormack, G: Dynamic Inverted Index for a Distributed Full text Retrieval System. Tech. Rep MT-95-01, University of Waterloo, Feb-1995.
  2. Ajit Kumar Mahapatra, Sitanath Biswas,"Inverted Index: Types and techniques", International journal of Computer science Issues, Volume-8,Issue-4, No. 1, July 2011.
  3. Ding, C. , A Similarity-based Probability Model for Latent Semantic Indexing, Proceedings of the 22nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 1999, pp. 59–65.
  4. Mark de Berg, Marc van Kreveld, Mark Overmars, and Otfried Schwarzkopf (2000). Computational Geometry (2nd revised ed. ). Springer-Verlag. ISBN 3-540-65620-0. Chapter 14: Quadtrees: pp. 291–306
  5. Stefan Büttcher, Charles L. A. Clarke, and Gordon V. Cormack. Information Retrieval: Implementing and Evaluating Search Engines. MIT Press, Cambridge, Mass. , 2010.
  6. WordNet-Online dictionary and hierarchical thesaurus Obtained through the Internet http://www. wordnetonline. com [accessed 28/12/2009]
  7. Ram Kumar Rana, Nidhi Tyagi, "A Novel Architecture of Ontology-based Semantic Web Crawler", International Journal of Computer Applications (0975 – 8887) Volume 44– No18, April 2012.
  8. N. Chauhan, A. K. Sharma, "Context Driven Focused Crawling: A New Approach to Domain-specific Web Retrieval", paper presented at International Conference on information & Communication Technology (IICT), July, 2007. Dehradun.
  9. Thomas R. Gruber, A translation approach to portable ontology specifications, Knowledge Acquisition 5 (1993), no. 2, 199–220.
  10. M. Ushold and M. Gruninger, Ontologies: Principles, methods and applications, The Knowledge Engineering Review, 1996.
  11. Oren Zamir and Oren Etzioni. Web Document Clustering: Afeasibility demonstration. In the proceedings of SIGIR, 1998.
  12. Changshang Zhou, Wei Ding, Na Yang, Double Indexing Mechanism of Search Engine based on Campus Net, Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing (APSCC'06).
  13. Sajendra Kumar, Ram Kumar Rana, Pawan Singh, "A Semantic Query Transformation Approach Based on Ontology for Search Engine", International Journal on Computer Science and Engineering (IJCSE), May 2012. (688-693).
Index Terms

Computer Science
Information Sciences

Keywords

IR Indexing Semantic index Ontology Semantic search