Universiti Teknologi Malaysia Institutional Repository

Query optimization in relevance feedback using hybrid GA-PSO for effective web information retrieval

Ibrahim, Siti Nurkhadijah Aishah and Selamat, Ali and Selamat, Mohd Hafiz (2009) Query optimization in relevance feedback using hybrid GA-PSO for effective web information retrieval. In: Proceedings - 2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009. Institute of Electrical and Electronics Engineers, New York, 91 -96. ISBN 978-076953648-4

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Official URL: http://dx.doi.org/10.1109/AMS.2009.95

Abstract

Due to the rapid growth of web pages available on the Internet recently, searching a relevant and up-to-date information has become a crucial issue. Conventional search engines use heuristics to determine which web pages are the best match for a given keyword. Results are obtained from a database that is located at their local server to provide fast searching. However, to search for the relevant and related information needed is still difficult and tedious. By using the genetic algorithm (GA) in relevance feedback, this paper presents a model of hybrid GA-Particle Swarm Optimization (HGAPSO) based query optimization for Web information retrieval. We expanded the keywords to produce the new keywords that are related to the user search. Experimental results demonstrate that it is very effective to improve the search of the relevant web pages using the HGAPSO.

Item Type:Book Section
Additional Information:2009 3rd Asia International Conference on Modelling and Simulation, AMS 2009; Bandung, Bali; 25 May 2009 through 26 May 2009
Uncontrolled Keywords:best match, local servers, query optimization, rapid growth, relevance feedback, web information retrieval, web page
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:13078
Deposited By: Liza Porijo
Deposited On:18 Jul 2011 01:43
Last Modified:18 Jul 2011 01:43

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