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Reseach Article

A Comparative Study on Approaches of Vector Space Model in Information Retrieval

Published on August 2013 by Jitendra Nath Singh, Sanjay Kumar Dwivedi
International Conference on Reliability, Infocom Technology and Optimization
Foundation of Computer Science USA
ICRITO - Number 1
August 2013
Authors: Jitendra Nath Singh, Sanjay Kumar Dwivedi
b79a3862-7975-4236-b213-a3742511b406

Jitendra Nath Singh, Sanjay Kumar Dwivedi . A Comparative Study on Approaches of Vector Space Model in Information Retrieval. International Conference on Reliability, Infocom Technology and Optimization. ICRITO, 1 (August 2013), 36-40.

@article{
author = { Jitendra Nath Singh, Sanjay Kumar Dwivedi },
title = { A Comparative Study on Approaches of Vector Space Model in Information Retrieval },
journal = { International Conference on Reliability, Infocom Technology and Optimization },
issue_date = { August 2013 },
volume = { ICRITO },
number = { 1 },
month = { August },
year = { 2013 },
issn = 0975-8887,
pages = { 36-40 },
numpages = 5,
url = { /specialissues/icrito/number1/13053-1306/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Reliability, Infocom Technology and Optimization
%A Jitendra Nath Singh
%A Sanjay Kumar Dwivedi
%T A Comparative Study on Approaches of Vector Space Model in Information Retrieval
%J International Conference on Reliability, Infocom Technology and Optimization
%@ 0975-8887
%V ICRITO
%N 1
%P 36-40
%D 2013
%I International Journal of Computer Applications
Abstract

The vector space model is one of the classical and widely applied information retrieval models to rank the web page based on similarity values. The retrieval operations consist of cosine similarity function to compute the similarity values between a given query and the set of documents retrieved and then rank the documents according to the relevance. In this paper, we are presenting different approaches of vector space model to compute similarity values of hits from search engine for given queries based on terms weight. In order to achieve the goal of an effective evaluation algorithm, our work intends to extensive analysis of the main aspects of Vector space model, its approaches and provides a comprehensive comparison for Term-Count Model, Tf-Idf model and Vector space model based on normalization.

References
  1. Shalton, G; Wong, A; Yang, C. S. : A vector space Model for automatic indexing, Communications of the ACM, Volume 18 and Issue 11:1975.
  2. Sanjay Kumar Dwivedi, Jitendra Nath Singh, and Rajesh Gotam Information Retrieval Evaluative Model, FTICT 2011: Proceedings of the 2011, International conference on Future Trend in Information & Communication Technology, Ghaziabad, India: 2011.
  3. Yi Shang Longzhuang Li: Precision Evaluation of Search Engines, World Wide Web: 2002.
  4. D. L. Lee, H. Chuang, and K. Seamons. Document ranking and the vector space model, IEEE Transactions on Software, 14(2): 1997.
  5. Chris Buckley. The importance of proper weighting methods, In M. Bates, editor, Human Language Technology. Morgan Kaufman: 1993.
  6. Longzhuang Li, Yi Shang A new statistical method for performance evaluation of search engines. ICTAI: 2000.
  7. Longzhuang Li, Yi Shang A new method for automatic performance comparison of search engines. World Wide Web: 2000.
  8. Chu, H. & Rosenthal: "Search engines for the World Wide Web: A comparative study and evaluation methodology". In Proceedings of the 59th Annual Meeting of the American Society for Information Science, Baltimore, 1996.
  9. Gerald Salton and Chris Buckley. Term weighting approaches in automatic text retrieval. Information Processing and Management, 24(5): Is-sue 5. 1988.
  10. G. Salton and C. Buckley, "Improving Retrieval Performance by Relevance Feedback," J. Amer. Soc. for Information Science, Vol. 41, No. 4, 199
  11. Jitendra Nath Singh & Sanjay Kumar Dwivedi: Analysis of Vector Space Model in Information Retrieval. Proceedings (IJCA) on National Conference on Communication Technologies & its impact on Next Generation Computing 2012 CTNGC (2):14-18:2012.
  12. Lee, D. l. ; Huei Chuang; Seamons, K. ; "Document ranking and the Vector-space model," Software, IEEE, vol. 14, no. 2, Pp. 67-75, Mar/April. 1997
Index Terms

Computer Science
Information Sciences

Keywords

Vector Space Model Information Retrieval Tf-idf Term- Frequency Cosine Similarity