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Reseach Article

Improved Indexing Technique for Information Retrieval based on Ontological Concepts

Published on December 2015 by Komal Shivaji Mule, Arti Waghmare
National Conference on Advances in Computing
Foundation of Computer Science USA
NCAC2015 - Number 4
December 2015
Authors: Komal Shivaji Mule, Arti Waghmare
acd650cd-c2a5-421a-977f-0d87ac7b6228

Komal Shivaji Mule, Arti Waghmare . Improved Indexing Technique for Information Retrieval based on Ontological Concepts. National Conference on Advances in Computing. NCAC2015, 4 (December 2015), 5-9.

@article{
author = { Komal Shivaji Mule, Arti Waghmare },
title = { Improved Indexing Technique for Information Retrieval based on Ontological Concepts },
journal = { National Conference on Advances in Computing },
issue_date = { December 2015 },
volume = { NCAC2015 },
number = { 4 },
month = { December },
year = { 2015 },
issn = 0975-8887,
pages = { 5-9 },
numpages = 5,
url = { /proceedings/ncac2015/number4/23377-5043/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computing
%A Komal Shivaji Mule
%A Arti Waghmare
%T Improved Indexing Technique for Information Retrieval based on Ontological Concepts
%J National Conference on Advances in Computing
%@ 0975-8887
%V NCAC2015
%N 4
%P 5-9
%D 2015
%I International Journal of Computer Applications
Abstract

Ontology has a richer internal structure as it includes relations and constraints between the concepts. Ontology can be used for information retrieval. Ontology is a halfway determination of a conceptual vocabulary to be utilized for formulating knowledge-level hypotheses around a domain of discourse. The key part of ontology is to help knowledge sharing and reuse. The process of allotting descriptions to documents in an IRS is called indexing. In previous system zone based indexing is introduced which has certain drawbacks. It helps finding results of user's query with exact match. A new technique is proposed which improves results. In this technique web pages are stored in xml database. Zones are formed in database. In case exact match is not found in xml database using zone based indexing then proximity of keyword is retrieved from the n-ary tree which is constructed using ontology. WordNet is used as dictionary for finding related words similar to user's query. A separate dictionary is created for words that are not present in WordNet. This application can be implemented in Libraries for access of books. Even if exact match is not available then also some of the related books can be retrieved. The aim of proposed system is to achieve higher Retrieval Status Value.

References
  1. Rajeswari Mukesh, Sathish Kumar Penchala, and Anupama K. Ingale. Ontology Based Zone Indexing Using Information Retrieval Systems. S. Unnikrishnan, S. Surve, and D. Bhoir (Eds. ): ICAC3 2013, CCIS 361, pp. 181–186, 2013.
  2. Saruladha, K. , Aghila, G. , Penchala, S. K. : Design of New Indexing Techniques Based on Ontology for Information Retrieval Systems. In: Das, V. V. , Vijaykumar, R. (eds. ) ICT 2010. CCIS, vol. 101, pp. 287–291. Springer, Heidelberg (2010)
  3. Troels Andreasen, Henrik Bulskov,"Conceptual querying through ontologies", Fuzzy Sets and Systems 160 (2009) 2159 – 2172, Elsevier
  4. S. Geethalakshmi, S. Umamaheswari , "An Efficient Technique for Multikeyword based Search and Retrieval of Cloud Data", 2014 International Conference on Recent Trends in Information Technology.
  5. Robin Sharma, Ankita Kandpa,Priyanka Bhakuni,Rashmi Chauhan,R. H. Goudar,Asit Tyagi,"Web Page Indexing through Page Ranking for Effective Semantic Search",Proceedings of 7thInternational Conference on Intelligent Systems and Control (ISCO 2013).
  6. Santosh K. Vishwakarma, Kamaljit I. Lakhtaria, Divya Bhatnagar, Akhilesh K. Sharma,"An efficient approach for inverted index pruning based on document relevance",2014 Fourth International Conference on Communication Systems and Network Technologies.
  7. Vandana Dhingra, Komal Kumar Bhatia,"SemIndex: Efficient Indexing Mechanism for Ontologies "2014 IEEE
  8. Lachtar Nadia, "Design and implementation of information retrieval system based ontology", 2014 IEEE
  9. Rupali Chandsarkar, Radha Shankarmani, Prachi Gharpure "Information Retrieval System: for Skill set Improvement in Software Projects ",2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA)
  10. Komal S. Mule, Prof. Arti Waghmare, "Review On Ontology Based Techniques In Information Retrieval Systems ", Multidisciplinary Journal of Research in Engineering and Technology, Volume 1,Issue 3, Pg. 273-278
  11. Thomas R. Gruber, "A Translation Approach to Portable Ontology Specifications ", Knowledge Systems Laboratory Technical Report KSL 92-71
  12. Suruchi Chawla , Dr Punam Bedi, "Improving Information Retrieval Precision by Finding Related Queries with similar Information Need using Information Scent ", First International Conference on Emerging Trends in Engineering and Technology, 2008.
  13. Qing Chen, "Towards Web-based Information Retrieval in Grid Environment",Social Science Foundation of Hubei Province, IEEE,2010.
Index Terms

Computer Science
Information Sciences

Keywords

Information Retrieval ontology Rsv N-ary Zone Based Indexing.