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Precision at K in Multilingual Information Retrieval

by Pothula Sujatha, P. Dhavachelvan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 24 - Number 9
Year of Publication: 2011
Authors: Pothula Sujatha, P. Dhavachelvan
10.5120/2990-3929

Pothula Sujatha, P. Dhavachelvan . Precision at K in Multilingual Information Retrieval. International Journal of Computer Applications. 24, 9 ( June 2011), 40-43. DOI=10.5120/2990-3929

@article{ 10.5120/2990-3929,
author = { Pothula Sujatha, P. Dhavachelvan },
title = { Precision at K in Multilingual Information Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 24 },
number = { 9 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 40-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume24/number9/2990-3929/ },
doi = { 10.5120/2990-3929 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:10:34.159266+05:30
%A Pothula Sujatha
%A P. Dhavachelvan
%T Precision at K in Multilingual Information Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 24
%N 9
%P 40-43
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Information Retrieval (IR) is used to store and represent the knowledge and the retrieval of information relevant for a special user query. Multilingual Information Retrieval (MLIR) system helps the users to pose the query in one language and retrieve the documents in more than one language. One of the basic performance measures of IR systems is Precision. While this measure work well in monolingual web retrieval, not suitable for CLIR (Cross-lingual Information Retrieval) or MLIR where two or more languages are involved. This paper proposed a metric which measures Precision at K which is the proportion of relevant documents in the first K positions when more than one document languages involved in the retrieval system i.e. MLIR. Experimental results demonstrate that the proposed metric is effective in systems where more than one document languages involved in the retrieval.

References
  1. Oard, D.W. and Dorr, B.J., 1996. A Survey of Multilingual Text Retrieval. Technical Report UMIACS-TR-96-19, University of Maryland, Institute for Advanced Computer Studies.
  2. Wang, J.-H., Teng, J.-W., Lu, W.-H., & Chien, L.-F. (2006). Exploiting the Web as the multilingual corpus for unknown query translation. Journal of the American Society for Information Science and Technology, 57, 660–670.
  3. Qin, J., Zhou, Y., Chau, M., & Chen, H. (2006). Multilingual Web retrieval: An experiment in English–Chinese business intelligence. Journal of the American Society for Information Science and Technology, 57, 671–683.
  4. Saracevic, T. Evaluation of Evaluation in Information Retrieval, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 137-146, 1995.
  5. Harman, D. Overview of the Second Text Retrieval Conference (TREC-2), Text Retrieval Conference-2, Gaithersburg, MD, National Institute of Standards and Technology Special Publication 500-215, March, 1994.
  6. Walid Magdy, Gareth J. F. Jones: PRES: a score metric for evaluating recall-oriented information retrieval applications. Dublin City University, 33rd Annual ACM SIGIR Conference 2010, 611-618.
  7. Donald A. Metzler, W. Bruce Croft, and Andre McCallum: Direct Maximization of Rank-Based Metrics for Information Retrieval. July 16, Published at CIIR 2005.
  8. Olivier Chapelle, Mingrui Wu: Gradient descent optimization of smoothed information retrieval metrics. Learning To Rank For Information Retrieval, Volume 13, Number 3, June 2010, 216-235.
  9. Filip Radlinski, Nick Craswell: Comparing the sensitivity of information retrieval metrics, SIGIR '10: Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval, July 2010, 667-674.
  10. G.V. Cormack and T.R. Lynam,: Validity and power of t-test for comparing MAP and GMAP. In Proc. SIGIR, 2007, pp.753-754.
  11. W. C. Lin and H. H. Chen. Merging mechanisms in multilingual information retrieval. Lecture notes in computer science, pages 175–186, 2003.
  12. Chapelle, O., Wu, M.: Gradient descent optimization of smoothed information retrieval metrics. Information Retrieval Journal (To appear) (2010)
  13. W.Li, D.Ganguly and G.J.F.Jones,: Enhanced Information Retrieval Using Domain-Specific Recommender Models, In Proceedings of the 3rd International Conference on the Theory of Information Retrieval (ICTIR'11), Bertinoro, Italy, September 2011
  14. Mandl, Thomas; Womser-Hacker, Christa; Ferro, Nicola; Di Nunzio, Giorgio (2008).: How Robust are Multilingual Information Retrieval Systems? In: Proceedings A CM Symposium on Applied Computing (SAC) Fortaleza, Brazil. pp. 1132-1136.
  15. Buckley, Chris; Voorhees, Ellen (2005): Retrieval System Evaluation. In: TREC: Experiment and Evaluation in Information Retrieval. Cambridge & London: MIT Press. pp. 53-75.
Index Terms

Computer Science
Information Sciences

Keywords

Multilingual Precision Recall Retrieval effectiveness

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