Research On Mobile User Behavior Analysis Based On GPS Data

In recent years,China's urbanization has been moving faster and faster,bringing economic growth while the traffic congestion on urban roads has become more serious.Therefore the taxis,buses and other vehicles location information through analysis and research of traffic congestion is more and more mature,but the study of personal mobile trajectory is not deep enough.And in daily life,the study of individual mobile trajectories has further meaning for the improvement of the quality of life and the prospect of business.To solve these problems,this article is based on Microsoft Asia research institute Geolife project to provide the user travel GPS data set,by combining the sequence pattern mining,data visualization,such as data processing method,analyzes the behavior of the mobile user research.Based on the trajectory for mobile users in the process of data mining,found the frequent pattern mining areas in space and time are greatly influenced by local data,and can't keep scheduling characteristics of the data.While sequential mode mining can maintain the timing of data,it is inefficient to calculate the amount of resources.A resident point mining method is therefore proposed to join,not only effective for the user interest information and keep the sequence of data,and the point of interest between the scheduling data by PrefixSpan algorithm for mining user effective sequential path.According to the analysis of experimental results show that the proposed method through experiment,through the use of the method,can be more comprehensive digging out the information associated with a GPS data behind.Combining with the mining results and the actual location information,found the user often go to the park,shopping malls and other fields,infer the user of the location of their working day dining and between may be a point of interest by means of transportation.According to the method,this paper analyses the user travel behaviour,can better use the users in real life the value behind the GPS data,can help companies better everyday life for the user services.