Understanding the nature of trajectories can help in analyzing their behavior. A spatiotemporal trajectory is a time stamped sequence generated by tracking the location of a moving object [1]. This sequence is represented by a series of space and time instances. A vast number of real-life applications are using mobile services sensors and Global Position Systems (GPS) to collect trajectory data. They apply trajectory mining techniques to discover knowledge which provides useful information for social networks, transportation systems, and urban computing. Several trajectory data mining techniques have been proposed such as pattern mining, clustering, classification, time series analysis, and anomaly detection. These techniques can help the city to detect road networks by tracing the movement of people in this city [2]. Trajectory mining techniques can translate collected geospatial coordinates and transform them into text information such as points of interest
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