By Topic

Web Information Retrieval Using Particle Swarm Optimization Based Approaches

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Drias, H. ; Dept. of Comput. Sci., USTHB, Algiers, Algeria

When dealing with large scale applications, data sets are huge and very often not obvious to tackle with traditional approaches. In web information retrieval, the greater the number of documents to be searched, the more powerful approach required. In this work, we develop document search processes based on particle swarm optimization and show that they improve the performance of information retrieval in the web context. Two novel PSO algorithms namely PSO1-IR and PSO2-IR are designed for this purpose. Extensive experiments were performed on CACM and RCV1 collections. The achieved results exhibit the superiority of PSO2-IR on all the others in terms of scalability while yielding comparable quality.

Published in:

Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on  (Volume:1 )

Date of Conference:

22-27 Aug. 2011