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Number 4

An Overview of Search Engine Evaluation Strategies

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  • International Journal of Applied Information Systems
  • Foundation of Computer Science (FCS), NY, USA
  • Volume 1 - Number 4
  • Year of Publication: 2012
  • Authors: Shikha Goel, Sunita Yadav
  • 10.5120/ijais12-450156
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  • Shikha Goel and Sunita Yadav 2012. An Overview of Search Engine Evaluation Strategies. International Journal of Applied Information Systems. 1, 4 (February 2012), 7-10. DOI=http://dx.doi.org/10.5120/ijais450156 
  • @article{10.5120/ijais2017451568,
author = {Shikha Goel and Sunita Yadav},
title = {An Overview of Search Engine Evaluation Strategies},
journal = {International Journal of Applied Information Systems},
issue_date = {February 2012},
volume = {1},
number = {},
month = {February},
year = {2012},
issn = {},
pages = {7-10},
numpages = {},
url = {/archives/volume1/number4/79-0156},
doi = { 10.5120/ijais12-450156},
publisher = { xA9 2010 by IJAIS Journal},
address = {}
}

  • %1 450156
%A Shikha Goel
%A Sunita Yadav
%T An Overview of Search Engine Evaluation Strategies
%J International Journal of Applied Information Systems
%@ 
%V 1
%N 
%P 7-10
%D 2012
%I  xA9 2010 by IJAIS Journal

Abstract

In this paper we discuss suitability of the using an open source environment; OpenCV for providing effective solutions for complex image processing and vision algorithm for real time application for UG and PG students projects. Computer Vision (CV) applications require extensive knowledge of digital signal processing, mathematics, statistics and perception. OpenCV is an open source vision library suitable for such computer vision programs. It’s always benefits to students to learn theoretical aspects of CV concepts by practicing in labs and getting hand-on expertise. In this paper, we describe our experience of using open source library for post-gradates and undergraduate students’ teaching. We also report the experience of developing the projects based on computer vision to Bachelor of Engineering in Information Technology (BE-IT) and Master of Engineering in Information Technology (ME-IT) courses. Initial tutorials designed help students to understand basic concepts of computer vision. Small applications development gives lot of confidence in executing complex assignments and moderate level projects. Statistics shows that projects undertaken by students had increased due to extensive practice on openCV environment. Finally we describe few example project and dissertation submitted in last two years by the students.

References

  1. Sergey Brin and Lawrence Page., (1998). “The Anatomy of a Large Scale Hyper textual Web Search Engine”, Computer Networks and ISDN Systems, pp.107-117.
  2. D.C. Free Net – ServInt Internet Services- “Working With Search Engine”.
  3. Addison Wesley., (2008).” Evaluating Search Engines”, pp.1-40.
  4. Jinbiao Hou., (2009). “Research on Design of an Evaluation System of Search Engine”, ETP International Conference on Future Computer and Communication,pp.12-18.
  5. Abdur Chowdhury, Ian Soboroff., (2002). “Automatic Evaluation of World Wide Web Search Services”,ACM, pp.421-422.
  6. Himanshu Sharma, Bernard J. Jansen., (2005).”Automated Evaluation of Search Engine Performance via Implicit User Feedback” The Pennsylvania State University,ACM,pp.649-650.
  7. Maninder Kaur, Nitin Bhatia, Sawtantar Singh., (2011).” Web Search Engines Evaluation Based on Features And End-User Experience”, International Journal of Enterprise Computing and Business Systems,Vol. 1 issue 2.
  8. Ya-Lan Chuang, Ling-Ling Wu., (2007).”User-Based Evaluations of Search Engines: Hygiene Factors and Motivation Factors, National Taiwan University, Proceedings of the 40th Hawaii International Conference on System Sciences, pp. 1-10.
  9. Longzhuang Li, Yi Shang, and Wei Zhang, “Relevance Evaluation of Search Engines Query Results” University of Missouri-Columbia.
  10. Liwen Vaughan., (2004)” New measurements for search engine evaluation proposed and tested” Information Processing and Management, Vol. 40, No. 4, pp. 677-691
  11. Gordon & Pathak., (1999).“Finding information on the World Wide Web: the retrieval effectiveness of search engines”. Information Processing and Management , pp. 141-180.
  12. Georges Dupret ,Vanessa Murdock, Benjamin Piwowarski., (2007).”Web search evaluation using click throughdata and a user model.
  13. Rashid Ali,M.M. Sufyan Beg., (2009).”Automated Performance Evaluation of Web Search System using rough set based rank aggregation”Proceedings of the first international conference on Intelligent Human Computer Interaction, Springer, pp.344-358.
  14. Hamid Sadeghi.,(2011). “Automatic Performance Evaluation of Web search Engines using judgements of Meta search Engines”, Online Information Review,ISSN:1468-4527,Emerald Publishing Limited, pp.957-971.

Keywords

Search Engine, Automatic Evaluation, User Feedback, Search query, Web search services, precision

Index Terms

Computer Science
Information Sciences