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 | |