By Topic

A novel content based and social network aided online spam short message filter

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yang Yu ; Fujian Key Lab. of Sci. & Eng. Comput., Fuzhou Univ., Fuzhou, China ; Yuzhong Chen

With the rapid development of mobile SMS (short message service), spam messages have grown explosively which trouble our daily lives seriously and lead to the loss of telecom operators. In this paper, an online spam filter based on the analysis of two criteria of content representations and relationship between the senders and receivers in social network is proposed. A Naïve Bayesian classifier is used to build up the filter including both the content features and social network features. We use the data provided by a partner telecom operator to do the experiments. The results show that our model is effective and satisfies all the requirements of our partner and will be deployed recently.

Published in:

Intelligent Control and Automation (WCICA), 2012 10th World Congress on

Date of Conference:

6-8 July 2012