Data Mining in Mobile Social Network from SMS Messages

Abstract

Mobile phone is one of the most prevalent communication tools today with the popularity of mobile devices and wireless technologies. Mobile social network systems are increasingly available. A mobile social network plays an essential role as the spread of information and relationship. Mining the popular SMS messages in a short period of time is very valuable. Traditional mining method is not suitable for this very large scale dataset. In this paper, we present a mining approach based on Map-Reduce parallel framework. Experimental results show that the final dataset of popular messages is very small with high sending coverage ratio. Empirical studies on a large real-world mobile social network show that performance of our algorithm.