关于用户兴趣点与路径提取矫正的研究

he user's living habits are closely related to the trajectory of the movement. Therefore, the academic community often through the study of the user's mobile rules to mine the user's behavior habits. Based on GPS data, this paper proposes an algorithm of user interest point clustering and user moving path extraction and rectification. Compared with the traditional solutions, this paper mainly has the following contributions: 1), based on the DBSCAN algorithm, the interest point clustering algorithm is designed, which can solve the problem of GPS data's heterogeneity, dispersion and drift;2), a user path extraction algorithm based on temporal and spatial rules is proposed, which can quickly and accurately extract the user's moving route; 3), the path correction algorithm based on map matching has been designed, which greatly reduces the error of position drift. The experimental results show that the proposed scheme can effectively solve the problems of trajectory data's heterogeneity, dispersion and drift, greatly improves the quality of interest point clustering and path extraction, has great value for engineering application and user movement research.?????