| With the development of information and communication technology and positioning technology, the tracking technology has rapidly improved. And the combination of GNSS, GSM, WIFI, RFID technology and communication technology, can achieve the goal of real-time tracking. Mobile phone has become an indispensable tool for people’s daily life, and meanwhile, a lot of mobile phones have equipped with GPS and other positioning devices, which can accurately determine the user’s current position. GSM can record user’s location while providing communication services for people. The mobile communications service provider has accumulated a large number of its consumer’s location data, and these data can unprecedentedly provide use with a wealth of data resources as we exploring the laws of user’s travel. To be more specific, user’s daily activity and movement will leave electronic imprint in the repository of wireless communication service provider. Along with more and more mobile phone usage and increasing positioning accuracy, mining the potential value of these records became possible.As movement data is a kind of trajectory, this thesis will carry out the flowing study based on mobile phone location data focusing on the theme of mining users’ travel rules.(1) Representation method of trajectory data.The essence of the trajectory data is spatial-temporal data, which is different from the general transaction data and the geographic data. It is complex. How to reasonably and effectively express trajectory data to make it easy to analyze and understand is a challenging task. After examining the existing trajectory data model, a method for the expression of location data in a low positioning accuracy is provided.(2) Extraction of trajectory’s characteristic informationLocation data has its own characteristics, and these characteristics objectively record the characteristic of user’s movement. This paper firstly studied the characteristics of trajectory data, and then explored the extraction method of feature information of the trajectory derived from cell of origin positioning technology.(3) Semantization of trajectory Trajectory is a record of people’s movement, but it cannot fully resemble movement law if we just study from the trajectory itself. Combined with semantic information, the depth travel pattern can be learned. Therefore, this article studied the method of how to give trajectory semantic information by providing two method of geographical semantization. One is based on the geographical location of the POI tags. And another, which is suitable for positioning method of origin of cell, is based on cell phone traffic data.(4) Algorithms of exploring the users’ travel rulesBased on the semantic information of trajectory, how to analyze users’ travel is studied. The article explored user’s movement behavior based on a method called Apriori algorithm, a frequent common used itemset mining algorithm.On the basis of the studies mentioned above, the visualization analysis platform of user travel behavior is achieved based on ArcGIS and secondary development method. Based on cellphone location data for7months (from2011-1-1to2011-8-1) of a typical user, we carried out an experiment to analyze his movement behavior. Result of the research will benefit the public sector of the community by providing decision support on the layout of the city, on solving the traffic jam problem, and the company by providing support for business conduct, and as well as personal travel by providing location-based services... |
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