• DocumentCode
    3725286
  • Title

    SMS spam detection for Indian messages

  • Author

    Sakshi Agarwal;Sanmeet Kaur;Sunita Garhwal

  • Author_Institution
    Department of Computer Science, Thapar University, Patiala, India
  • fYear
    2015
  • Firstpage
    634
  • Lastpage
    638
  • 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"
  • Publisher
    ieee
  • Conference_Titel
    Next Generation Computing Technologies (NGCT), 2015 1st International Conference on
  • Type

    conf

  • DOI
    10.1109/NGCT.2015.7375198
  • Filename
    7375198