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

dc.contributor.author	Mansur, Munirul
dc.contributor.author	UzZaman, Naushad
dc.contributor.author	Khan, Mumit
dc.date.accessioned	2010-10-21T09:14:58Z
dc.date.available	2010-10-21T09:14:58Z
dc.date.copyright	2006
dc.date.issued	2006
dc.identifier.uri	http://hdl.handle.net/10361/623
dc.description	Includes bibliographical references (page 7).
dc.description.abstract	In 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.statementofresponsibility	Munirul Mansur
dc.description.statementofresponsibility	Naushad UzZaman
dc.description.statementofresponsibility	Mumit Khan
dc.format.extent	7 pages
dc.language.iso	en	en_US
dc.publisher	BRAC University	en_US
dc.title	Analysis of N-Gram based text categorization for Bangla in a newspaper	en_US
dc.type	Article	en_US
dc.contributor.department	Center for Research on Bangla Language Processing (CRBLP), BRAC University