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

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dc.contributor.authorMansur, Munirul
dc.contributor.authorUzZaman, Naushad
dc.contributor.authorKhan, Mumit
dc.contributor.departmentCenter for Research on Bangla Language Processing (CRBLP)
dc.date.accessioned2010-10-21T09:14:58Z
dc.date.available2010-10-21T09:14:58Z
dc.date.copyright2006
dc.date.issued2006
dc.descriptionIncludes bibliographical references (page 7).
dc.description.abstractIn this paper, we study the outcome of using ngram based algorithm for Bangla text categorization. To analyze the efficiency of this methodology we used one year Prothom-Alo news corpus. Our results show that n-grams of length 2 or 3 are the most useful for categorization. Using gram lengths more than 3reduces the performance of categorization.en_US
dc.description.statementofresponsibilityMunirul Mansur
dc.description.statementofresponsibilityNaushad UzZaman
dc.description.statementofresponsibilityMumit Khan
dc.format.extent7 pages
dc.identifier.urihttp://hdl.handle.net/10361/623
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.titleAnalysis of N-Gram based text categorization for Bangla in a newspaperen_US
dc.typeArticleen_US

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