Trajectory Outlier Detection Algorithm Based on Structural Features
نویسندگان
چکیده
As the development of location based service, such as GPS and RFID, a great volume of trajectory data can be collected. As a result, mining knowledge from these data has become an attractive topic. The trajectory outlier detection algorithm, proposed in this paper, can be used to detect trajectory outliers by comparing the structure between each trajectory segment pairs. Firstly, a new concept of trajectory structure, taking full advantage of trajectory implicit features, is introduced to analyze trajectory similarity. Secondly, an outlier detection algorithm is put forward to match the two segments by computing their structural similarity. Thirdly, segment and trajectory outliers are detected by analyzing their both external and internal features. Experiments on real dataset demonstrate the efficiency, effectiveness of the proposed algorithm, feature sensitivity can be adjusted by the parameters flexibly, and the detected outliers are more practical significant.
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