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Optimizing Search Engine Result using Intelligent Model

by Hamada. M.zahera, Gamal. F. Elhady, Arabi. E. Keshk
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 1
Year of Publication: 2012
Authors: Hamada. M.zahera, Gamal. F. Elhady, Arabi. E. Keshk

Hamada. M.zahera, Gamal. F. Elhady, Arabi. E. Keshk . Optimizing Search Engine Result using Intelligent Model. International Journal of Computer Applications. 50, 1 ( July 2012), 30-37. DOI=10.5120/7736-0788

@article{ 10.5120/7736-0788,
author = { Hamada. M.zahera, Gamal. F. Elhady, Arabi. E. Keshk },
title = { Optimizing Search Engine Result using Intelligent Model },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 1 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 30-37 },
numpages = {9},
url = { },
doi = { 10.5120/7736-0788 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:47:11.223923+05:30
%A Hamada. M.zahera
%A Gamal. F. Elhady
%A Arabi. E. Keshk
%T Optimizing Search Engine Result using Intelligent Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 1
%P 30-37
%D 2012
%I Foundation of Computer Science (FCS), NY, USA

Many search engine users face problems while retrieving their required Information. For example, a user may find it is difficult to retrieve sufficient relevant information because he use too few keywords to search or the user is inexperienced and do not search using proper keywords and the search engine is not able to receive the user real meaning through his given keywords. Also, due to the recent improvements of search engines and the rapid growth of the web, the search engines return a huge number of web pages, and then the user may take long time to look at all of these pages to find his needed information. The problem of obtaining relevant results in web searching has been tackled by several approaches. Although very effective techniques are currently used by the most popular search engines, but no a priori knowledge on the user's desires beside the search keywords is available. In this paper, we present an approach for optimizing the search engine results using artificial intelligence techniques such as document clustering and genetic algorithm to provide the user with the most relevant pages to the search query. The proposed method uses the Meta-data that is coming from the user preferences or the search engine query log files. These data is important to find the most related information to the user while searching the web. Finally, the method implementation and some of the experimental results are presented with the conclusion of this research study.

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Index Terms

Computer Science
Information Sciences


Search Engines Information Retrieval World Wide Web Document Clustering Genetic Algorithm