Mining human mobility patterns from social geo-tagged data

被引：49

作者：

Comito, Carmela ^{[1
]}

Falcone, Deborah ^{[2
]}

Talia, Domenico ^{[2
]}

机构：

[1] ICAR CNR, Arcavacata Di Rende, CS, Italy

[2] Univ Calabria, DIMES, Arcavacata Di Rende, CS, Italy

来源：

PERVASIVE AND MOBILE COMPUTING | 2016年 / 33卷

关键词：

Trajectory pattern mining; Geo-social data; Human mobility;

D O I：

10.1016/j.pmcj.2016.06.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Online social networks allow users to tag their posts with geographical coordinates collected through the GPS interface of smart phones. The time- and geo-coordinates associated with a sequence of posts/tweets manifest the spatial-temporal movements of people in real life. This paper aims to analyze such movements to discover people and community behavior. To this end, we defined and implemented a novel methodology to mine popular travel routes from geo-tagged posts. Our approach infers interesting locations and frequent travel sequences among these locations in a given geo-spatial region, as shown from the detailed analysis of the collected geo-tagged data. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：91 / 107

页数：17

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