Title: Automatic Text Categorization of News Articles
To categorize the data reduces the access time. Nowadays, the Internet is one of the biggest data resources. However, most of the data on the Internet is written in natural language. To use the Internet more efficiently, it needs to be categorized. The amount of data and its increment rate is so high that this process cannot be done by hand. Hence, the necessity for automatic text categorization systems is increasing. In contrast to other languages, there is not much study on Turkish texts. In this study, a system is developed for Automatic Text Categorization of News Articles. The articles are classified into 5 different classes and a 76% success ratio is achieved.
Homepage: http://www.kemik.yildiz.edu.tr/veri_kumelerimiz.html
@inproceedings{amasyali-yildirim-2004-otomatik,
title={Otomatik haber metinleri s{\i}n{\i}fland{\i}rma},
author={Amasyal{\i}, MF and Y{\i}ld{\i}r{\i}m, T},
booktitle={2004 12th Signal Processing and Communications Applications Conference (SIU)},
pages={224-226},
year={2004},
organization={IEEE}
}