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

Improving the Information Retrieval System through Effective Evaluation of Web Page in Client Side Analysis

by Rekha.C, Usharani.J, Dr. K. Iyakutti
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 15 - Number 6
Year of Publication: 2011
Authors: Rekha.C, Usharani.J, Dr. K. Iyakutti
10.5120/1950-2608

Rekha.C, Usharani.J, Dr. K. Iyakutti . Improving the Information Retrieval System through Effective Evaluation of Web Page in Client Side Analysis. International Journal of Computer Applications. 15, 6 ( February 2011), 35-39. DOI=10.5120/1950-2608

@article{ 10.5120/1950-2608,
author = { Rekha.C, Usharani.J, Dr. K. Iyakutti },
title = { Improving the Information Retrieval System through Effective Evaluation of Web Page in Client Side Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 15 },
number = { 6 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume15/number6/1950-2608/ },
doi = { 10.5120/1950-2608 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:03:28.771428+05:30
%A Rekha.C
%A Usharani.J
%A Dr. K. Iyakutti
%T Improving the Information Retrieval System through Effective Evaluation of Web Page in Client Side Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 15
%N 6
%P 35-39
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To improve the information retrieval system for user, programmers have to learn a user's preferences accurately. In order to optimize retrieval accuracy, modeling the users appropriately based on their preferences and personalizing search according to each individual user are important. Implicit feedback information improves the user modeling process. The advantage of implicit modeling is effectively improving the user model without extra effort of user. Several implicit feedback features are used to develop user modeling process. We present a new model to find a user's preferences from click through behavior and using the exposed preferences to adapt the search engine's ranking function for improving search service. In this proposed model, the combination of viewed and stored document summaries is used.

References
  1. M. Baldoni, C. Barigkui and N. Henze, “ Personalization for the semantic web”, Reasoning web, First international summer school, LNCS, 2005.
  2. Jintiyuk cho and Geehyak Lec, “New Techniques for data preprocessing Based on usage Logs for efficient web uses profiling at client size”, IEEE / WIC /ACM international conference on web intelligence and intelligent Agent Technology – Workshops, 2009.
  3. Xuehua Shen, Bin Tan, Chengziang Zhai, “ Implicit user modeling for personalized search, ACM 1 -59593 -140 -6/05/0010, 2005.
  4. D. Kelly and J. Teavan, “Implicit feedback for Inferring user preference”, A bibliography SIGIR forum 37(2); 18-28, 2003
  5. Eugene Agichtein, Eric Bril, Susan Dumais, “Improving web search Ranking by incorporating user behavior information” ACM 1-59593-369-7\06\0008.
  6. Semantic web personalization by Palakron Achananuparp, College of Information Science and Technology, Direxel University.
  7. Xiaojian Ding, Yuancheng Li，Yinliang Zhao, “A framework of user model based on Semi-supervised techniques”, IEEE International Conference on e-Business Engineering, 2008.
  8. Pradipta Biswas and Peter Robinson, “ A brief survey on user modeling in HCI
  9. Perugini, S. Goncalves, M.A and Fox E.A, “Recommander System Research. A connection centric survey , Journal of Intelligent Information System, Vol 23,no.2,PP.107-143,2004.
  10. X.Shen,B.Tan, and C.Zhai, “Context-Sensitive information retrieval using implicit feedback”, proceedings of SIGIR 2005, pages 43-50,2005.
  11. Xuehua Shen, Bin Tan , Cheng Xiang Zhai, “ Exploiting personal search history to improve search accuracy-personal Information management”, A SIGIR 2006 workshop.
  12. F-Gasparetli and A . Micarelli ,”User profile generation based on a memeory retrieval theory” in proceedings of the first international workshop on web personalization recommender systems and intelligent user Interfaces WPRSIUI 2005, reading UK Oct 2005.
  13. Ahu sieg , Bamshad mobasher, Robin burke, “Learning ontology-Based user profiles : A sermantic approach to personalized web search”, IEEE intelligent information Bulletion, Vol 8 no.1\ Nov 2007.
  14. T.Joachims, L.Granka,B.Pang, H.Hembrooke and G.Gay , “Accurately Interprating click through Data as conference on research. Proceedings of the ACM”, conference on research and development on information Retrieval (SIGIR),2005
  15. G.R .Xue, H.J. Zeng, Z.Chen ,Y. Yu, ,W.Y.Ma, W.S.Xi and W.G Fan, “Optimizing web search using web click through data”, in proceeding of the conference on information and knowledge management (CIKM),2004.
  16. Ganesan Velaythan, Seiji Yamada “Behavior-Based web page evaluation”,
  17. M.Claypool, D.Brown, P.Lee and M.Waseda, “Inferring user interest in IEEE Internet compiling”, 2001.
  18. S. Fox, K. Karnawat, M.mydland, S.T. Dumais and T.white, “Evaluating implicit measures to improve the search experience”, iIn ACM Transactions on information Systems, 2005.
  19. ]X. Shen, B. Tan, and C. Zhai, “UCAIR toolbar: A personalized search toolbar (Demo)”, in Proceedings of SIGIR 2005, page 681, 2005.
  20. My yahoo! http://mysearch
Index Terms

Computer Science
Information Sciences

Keywords

Information Retrieval Effective Evaluation Client Side

Powered by PhDFocusTM