基于轨迹划分与密度聚类的移动用户重要地点识别方法

doi:10.11896/j.issn.1002-137X.2019.08.004

Abstract

Abstract: As emerging spatial trajectory data,mobile user trajectory data can be used to analyze individual or group behavioral characteristics,hobbies and interests,and are widely used in smart cities,transportation planning,and anti-terrorism maintenance.In order to identify the important locations of mobile user from a huge data set,this paper proposed a trajectory division method based on the angle and distance offset.The method firstly extracts the important locations candidate set by trajectory division,and then further clusters the important locations through an improved density clustering algorithm,extracting the final important location of user.The experiment on Geolife trajectory data set and Foursquare data set shows that the important location identification method combining trajectory division and density clustering has higher accuracy than other existing important location identification method,which proves the feasibility and superiority of the proposed method

Key words: Density clustering, Important locations, Mobile user, Trajectory division

CLC Number:

TP181

YANG Zhen, WANG Hong-jun. Important Location Identification of Mobile Users Based on Trajectory Division and Density Clustering Method[J].Computer Science, 2019, 46(8): 23-27.

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Important Location Identification of Mobile Users Based on Trajectory Division and Density Clustering Method

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