Open AccessFramework for Urdu News Headlines Classification
Author(s) -
Kashif Ahmed,
Mubashir Ali,
Shehzad Khalid,
Muhammad Kamran
Publication year - 2016
Publication title -
journal of applied computer science and mathematics/journal of applied computer science
Language(s) - English
Resource type - Journals
eISSN - 2066-3129
pISSN - 1843-1046
DOI - 10.4316/jacsm.201601002
Subject(s) - urdu , computer science , linguistics , philosophy
Automatic text classification has great significance\udin the field of text mining and plays a pivotal role in areas such\udas spam filtering, news classification, noise reduction etc. It is\udevident from the literature that there is ample of research\udconducted for classifying text documents e.g. English news\udclassification, Persian text classification etc. but there is no\udcopious amount of work related to short Urdu text or Urdu\udnews headlines classification. Therefore, after examining various\udexisting news classification methodologies we propose an SVM\udbased framework in this paper for classification of Urdu news\udheadlines. This approach classifies Urdu news based on\udheadlines in their respective pre-defined categories by utilizing\udtheir feature vector’s maximum indexes. This proposed system\udis compared with existing state-of-the art techniques