移动计算以及定位技术的快速发展正在改变人们的生活方式,使人们可以随时随地上网,还带来了大量反映用户运动轨迹的GPS数据。为了收集和分析这些GPS数据,设计实现了一个基于GPS数据的用户生活规律挖掘系统。对于记录数据阶段,通过运行Android系统的智能手机收集GPS数据,并定时将GPS轨迹数据发送到后台服务器;而在挖掘阶段,基于不同用户的GPS数据,挖掘出停留点序列并且获取周期模式。在这里,停留点用来表示与用户行为关联的地点。在获取了停留点的序列后,就可以挖掘频繁周期模式并对这些模式进行分析。最后,通过实验证明系统在处理大量GPS数据时仍能够保证高效性和稳定性。
The fast development of positioning technology and mobile computing is changing the way people live. People can connect the interuet anytime and anywhere and it brings us amounts of GPS data representing the users' location histories. A system was designed to mine periodic behaviors on GPS data. In the stage of data collection, smartphones running on Android will be used to collect GPS data and then the data will be sent to a HqTP server at regular intervals. In the data mining stage, it is aimed to mine reference spot and understand the periodic pattern based on different users' GPS data. Also, stay points were used to represent the behaviors of users. With the sequence of stay points, frequent periodic patterns were mined and then these patterns were summarized. Finally, the experiments indicate our system shows efficient and stable performance with large numbers of GPS data.