Title :
SMS spam detection for Indian messages
Author :
Sakshi Agarwal;Sanmeet Kaur;Sunita Garhwal
Author_Institution :
Department of Computer Science, Thapar University, Patiala, India
Abstract :
The growth of the mobile phone users has led to a dramatic increase in SMS spam messages. Though in most parts of the world, mobile messaging channel is currently regarded as “clean” and trusted, on the contrast recent reports clearly indicate that the volume of mobile phone spam is dramatically increasing year by year. It is an evolving setback especially in the Middle East and Asia. SMS spam filtering is a comparatively recent errand to deal such a problem. It inherits many concerns and quick fixes from Email spam filtering. However it fronts its own certain issues and problems. This paper inspires to work on the task of filtering mobile messages as Ham or Spam for the Indian Users by adding Indian messages to the worldwide available SMS dataset. The paper analyses different machine learning classifiers on large corpus of SMS messages for Indian people.
Keywords :
"Mobile communication","Filtering","Mobile handsets","Electronic mail","Machine learning algorithms","Algorithm design and analysis","Measurement"
Conference_Titel :
Next Generation Computing Technologies (NGCT), 2015 1st International Conference on
DOI :
10.1109/NGCT.2015.7375198