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Analysis of N-Gram based text categorization for Bangla in a newspaper corpus

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dc.contributor.advisor Khan, Mumit
dc.contributor.author Mansur, Munirul
dc.date.accessioned 2010-09-06T06:29:41Z
dc.date.available 2010-09-06T06:29:41Z
dc.date.copyright 2006
dc.date.issued 2006-08
dc.identifier.other ID 02101043
dc.identifier.uri http://hdl.handle.net/10361/61
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, 2006. en_US
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (page 30).
dc.description.abstract The goal of any classification is to build a set of models that can correctly predict the class of different objects. Text categorization is one such application and can be used in many classification task, e.g. news categorization, language identification, authorship attribution, text genre categorization, recommendation systems etc. In this paper we analyze the performance of n-gram based text categorization for Bangla in a Bangladeshi newspaper, Prothom-Alo corpus. en_US
dc.description.statementofresponsibility Munirul Mansur
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 Analysis of N-Gram based text categorization for Bangla in a newspaper corpus 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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