An Efficient Approach Formulation of Social Groups of User Calls of GSM

We are living in a world of wireless technology. The most widely used wireless i.e. mobile computing device today is the Mobile phone, can be used not only for voice and data communications but also as a computing device running context aware applications. In this paper we present a model that based on GSM data base. The objective of this paper identifies social and suspicious groups based on Cell Id, IMSI, IMEI, date and time, Location Area, MCC and MNC. This information can be used by applications for the detection of users, user context, discovering of groups and relation between them using clustering technique of data mining. One of the vital means in dealing with these data is to classify or group them into a set of categories or clusters. We demonstrate that even without knowledge of observed cell tower locations, we can recognize mobility modes that are useful for several application domains. Our mobility detection system was evaluated with GSM traces from the everyday lives of three data collectors