CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Performance Assessment of AMRR and ADCG Metrics in MLIR and IR Systems

by Raju Korra, Pothula Sujatha, Prof.P.Dhavachelvan, Madarapu Naresh Kumar
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 24 - Number 2
Year of Publication: 2011
Authors: Raju Korra, Pothula Sujatha, Prof.P.Dhavachelvan, Madarapu Naresh Kumar
10.5120/2919-3851

Raju Korra, Pothula Sujatha, Prof.P.Dhavachelvan, Madarapu Naresh Kumar . Performance Assessment of AMRR and ADCG Metrics in MLIR and IR Systems. International Journal of Computer Applications. 24, 2 ( June 2011), 43-48. DOI=10.5120/2919-3851

@article{ 10.5120/2919-3851,
author = { Raju Korra, Pothula Sujatha, Prof.P.Dhavachelvan, Madarapu Naresh Kumar },
title = { Performance Assessment of AMRR and ADCG Metrics in MLIR and IR Systems },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 24 },
number = { 2 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume24/number2/2919-3851/ },
doi = { 10.5120/2919-3851 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:09:59.200437+05:30
%A Raju Korra
%A Pothula Sujatha
%A Prof.P.Dhavachelvan
%A Madarapu Naresh Kumar
%T Performance Assessment of AMRR and ADCG Metrics in MLIR and IR Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 24
%N 2
%P 43-48
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Multiple language documents retrieval is being done by using Multilingual Information Retrieval (MLIR) system. MLIR system deals with the use of queries in one language and retrieves the documents in various languages. The Query translation plays a central role in MLIR system research. We have used English as the source language and Hindi, French and German as the target languages. The experimental results are evaluated to analyze and compare the performance of proposed MLIR system metrics, Average Mean Reciprocal Rank (AMRR) and Average Discounted Cumulative Gain (ADCG), in Information Retrieval (IR) and MLIR system. Experimental results show that the performance of AMRR, ADCG in MLIR system has been improved 81.67%, 43.93% over IR system respectively.

References
  1. Jarvelin, K. and Kekal ainen, J.: Cumulated Gain-Based Evaluation of IR Techniques, ACM TOIS, Vol. 20, No. 4, pp. 422-446, 2002.
  2. Burges, C. et al.: Learning to Rank using Gradient Descent, Proceedings of ACM ICML 2005, pp. 89-96, 2005.
  3. Sakai, T.: On Penalising Late Arrival of Relevant Documents in Information Retrieval Evaluation with Graded Relevance, Proceedings of the First Workshop on Evaluating Information Access (EVIA 2007), pp.32-43, 2007. Available at: http://research.nii.ac.jp/ntcir/workshop/ OnlineProceedings6/EVIA/1.pdf.
  4. Sakai, T., Kando, N., Lin, C.-J., Mitamura, T., Shima, H., Ji, D., Chen, K.-H., and Nyberg, E.: Overview of the NTCIR-7 ACLIA IR4QA Task, NTCIR-7 Proceedings, pp.77-114, December 2008.
  5. Kekalainen, J. & Jarvelin, K. (2002). User-oriented evaluation methods for information retrieval: A case study based on conceptual models for query expansion. In: Lakemeyer, G. & Nebel, B. (Eds.) Exploring Artificial Intelligence in the New Millennium. San Francisco: Morgan Kaufmann Publishers, pp. 355 - 379. ISBN 1-55860-811-7.
  6. E.M. Voorhees (1999). "Proceedings of the 8th Text Retrieval Conference". TREC-8 Question Answering Track Report. pp. 77–82.
  7. Contributors: Christian Fluhr Robert E. Frederking Doug Oard Akitoshi Okumura, Kai Ishikawa, and Kenji Chapter 2 Multilingual (or Cross-lingual) Information Retrieval,Editors: Judith Klavans and Eduard Hovy Satoh http://www.cs.cmu.edu/~ref/mlim/chapter2.html
  8. Chen-Hsin Cheng, Reuy-Jye Shue, Hung-Lin Lee, Shu-Yu Hsieh, Guann-Cyun Yeh, & Guo-Wei Bian: AINLP at NTCIR-6: evaluations for multilingual and cross-lingual information retrieval Proceedings of NTCIR-6 Workshop Meeting, May 15-18, 2007, Tokyo, Japan.
  9. Dan Wu, Daqing He, Huilin Wang. “Cross-Language Query Expansion Using Pseudo Relevance Feedback.” Journal of the Chinese Society for Scientific and Technical Information. 29.2 (2010): 232-239.
  10. Qiang, Pu, Daqing He, Qi Li. "Query Expansion for Effective Geographic Information Retrieval." Evaluating Systems for Multilingual and Multimodal Information Access, 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark, Revised Selected Papers. Springer. 2009.
  11. Sakai, T.: New Performance Metrics based on Multigrade Relevance: Their Application to Question Answering, NTCIR-4 Proceedings, 2004.
  12. Sakai, T.: On the Reliability of Information Retrieval Metrics based on Graded Relevance, Information Processing and Management, Vol. 43, Issue. 2, pp. 531-548, 2007.
  13. Kekalainen, J.: Binary and Graded Relevance in IR evaluations - Comparison of the Effects on Ranking of IR Systems, Information Processing and Management, Vol. 41, pp. 1019-1033, 2005.
  14. Sakai, T. and Robertson, S.: Modelling a User Population for Designing Information Retrieval Metrics, Proceedings of the Second International Workshop on Evaluating Information Access (EVIA 2008), pp.30-41, December 2008.
  15. Tetsuya Sakai, Noriko Kando: On information retrieval metrics designed for evaluation with incomplete relevance assessments. Information Retrieval 11 (5):447-470(2008).
  16. Olivier Chapelle, Mingrui Wu: Gradient descent optimization of smoothed information retrieval metrics. Inf. Retr. 13(3): 216-235 (2010).
  17. Jianfeng Gao, Endong Xun, Ming Zhou, Changning Huang, Jian-Yun Nie, Jian Zhang: Improving Query Translation for Cross-Language Information Retrieval Using Statistical Models. SIGIR 2001: 96-104.
  18. Marcello Federico, Nicola Bertoldi: Statistical cross-language information retrieval using n-best query translations. SIGIR 2002: 167-174.
  19. Sakai, T.: Average Gain Ratio: A Simple Retrieval Performance Measure for Evaluation with Multiple Relevance Levels, ACM SIGIR 2003 Proceedings, pp.417-418, July 2003.
  20. Manoj Kumar Chinnakotla, Karthik Raman, and Pushpak Bhattacharyya: Multilingual PRF: English lends a helping hand. SIGIR 2010: 659-666.
Index Terms

Computer Science
Information Sciences

Keywords

MLIR Mean Reciprocal Rank Cumulative Gain Average Mean Reciprocal Rank Average Discounted Cumulative Gain

Powered by PhDFocusTM