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Abstract
Mobility prediction is defined as guessing the next access point(s) a mobile terminal will join so as to connect to a (wired or wireless) network. Knowing in advance where a terminal is heading for allows taking proactive measures so as to mitigate the impact of handovers and, hence, improve the network QoS. This thesis analyzes this topic from different points of view. Many studies introduced in this topic and each has a technique. prediction using data minig is one of them. Previous studies of data mining techniques did not manipulate GPS raw data. Preposed solution in this thesis uses GPS data to predict the location of moving users. Clustering and classification are used in this study