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Document clustering using swarm intelligence

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dc.contributor.advisor Ali, Abu Mohammad Hammad
dc.contributor.author Rizwan, Md. Adeeb
dc.date.accessioned 2013-04-30T18:14:23Z
dc.date.available 2013-04-30T18:14:23Z
dc.date.copyright 2012
dc.date.issued 2012-12
dc.identifier.other ID 09201029
dc.identifier.uri http://hdl.handle.net/10361/2381
dc.description This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2012. en_US
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (page 27).
dc.description.abstract With the recent rise in electronic data, and the pressing time needs of daily life, there is scope for a good document clustering system that can divide a set of documents into similar topic clusters. A lot of different algorithms have been attempted towards this end, from statistical learning methods to neural networks. In more recent years, there has been a growing interest in collective intelligence as often displayed in nature by ants and birds. We would like to do a survey of this last field, and look for possible applications of algorithms in this area for the document clustering problem. en_US
dc.description.statementofresponsibility Md. Adeeb Rizwan
dc.format.extent 27 pages
dc.language.iso en en_US
dc.publisher BRAC University en_US
dc.rights BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subject Computer science and engineering
dc.title Document clustering using swarm intelligence en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University
dc.description.degree B. Computer Science and Engineering


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