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Article:Web Search Result Personalization Using Web Mining

by Kavita D. Satokar, Prof..S.Z.Gawali
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 2 - Number 5
Year of Publication: 2010
Authors: Kavita D. Satokar, Prof..S.Z.Gawali
10.5120/665-933

Kavita D. Satokar, Prof..S.Z.Gawali . Article:Web Search Result Personalization Using Web Mining. International Journal of Computer Applications. 2, 5 ( June 2010), 29-32. DOI=10.5120/665-933

@article{ 10.5120/665-933,
author = { Kavita D. Satokar, Prof..S.Z.Gawali },
title = { Article:Web Search Result Personalization Using Web Mining },
journal = { International Journal of Computer Applications },
issue_date = { June 2010 },
volume = { 2 },
number = { 5 },
month = { June },
year = { 2010 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume2/number5/665-933/ },
doi = { 10.5120/665-933 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:50:10.365493+05:30
%A Kavita D. Satokar
%A Prof..S.Z.Gawali
%T Article:Web Search Result Personalization Using Web Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 2
%N 5
%P 29-32
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The information on the web is growing dramatically. The users have to spend lots of time on the web finding the information they are interested in. Today, he traditional search engines do not give users enough personalized help but provide the user with lots of irrelevant information. In this paper, we present a personalize Web search system, which can helps users to get the relevant web pages based on their selection from the domain list. Thus, users can obtain a set of interested domains and the web pages from the system. The system is based on features extracted from hyperlinks, such as anchor terms or URL tokens, user interest domains and past search results. Our methodology uses an innovative weighted URL Rank algorithm based on user interested domains and user query.

References
  1. M. Eirinaki, M. Vazirgiannis, “Web mining for Web personalization”, ACM Transactions on Internet Technology, 3(1), 2003, pp. 1–27.
  2. Ouyang Liubo, Li Xueyong, Li Guohui,Wamg Xin, “A Survey of Web Spiders Searching Strategies of Topic-specific Search Engine,” Computer Engineering, vol. 13, pp. 32-33, 46, 2004.
  3. van Rijsbergen, C.: Information Retrieval. Butterworths, London (1979) Second edition.
  4. Salton, G., McGill, M.: An Introduction to Modern Information Retrieval. McGraw-Hill, New York, NY (1983)
  5. Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Computer Networks 30 (1998) 107–117
  6. Kleinberg, J.: Authoritative sources in a hyperlinked environment. Journal of the ACM 46 (1999) 604–632
  7. G. Salton et al., “The SMART System—Experiments in Automatic Document Processing,” Prentice-Hall, Englewood Cliffs, N.J., 1971.
  8. Hidalgo-Herrero, M., Rodriguez, I., Rubio, F.: Testing learning strategies. In: ICCI ’05: Proceedings of the Fourth IEEE International Conference on Cognitive Informatics, Washington, DC, USA, IEEE Computer Society (2005) 212– 221
Index Terms

Computer Science
Information Sciences

Keywords

personalization recommendation interested domains collaborative filtering

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