| dc.contributor.author |
Mansur, Munirul |
|
| dc.date.accessioned |
2010-09-06T06:29:41Z |
|
| dc.date.available |
2010-09-06T06:29:41Z |
|
| dc.date.issued |
2006-08 |
|
| dc.identifier.other |
ID 02101043 |
|
| dc.identifier.uri |
http://hdl.handle.net/10361/61 |
|
| dc.description |
This thesis paper is a partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, BRAC University . |
en_US |
| 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.publisher |
School of Engineering and Computer Science (SECS) , BRAC University |
en_US |
| dc.title |
Analysis of N-Gram based text categorization for Bangla in a newspaper corpus |
en_US |
| dc.type |
Thesis |
en_US |