The mining of urban residents' activity rules based on mobile phone positioning data

被引：0

作者：

Zuo, Xiaoqing ^{[1
]}

Chen, Lei ^{[1
]}

Yu, Hongchu ^{[1
]}

机构：

[1] Zuo, Xiaoqing

[2] Chen, Lei

[3] Yu, Hongchu

来源：

Zuo, Xiaoqing | 1600年 / Sila Science, University Mah Mekan Sok, No 24, Trabzon, Turkey卷 / 32期

关键词：

Clustering algorithms - Pattern recognition - Cellular telephones;

D O I：

暂无

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学科分类号：

摘要：

Mobile phone positioning data with wide coverage provides very good data resources for the study of urban residents travel rules. According to the characteristics of mobile phone positioning data, propose a spatio-temporal clustering algorithm for mining stops of residents’ daily activities; on this basis, use Apriori algorithm for mining frequent travel path of the residents. Collecting 108 anonymous users’ mobile phone positioning data for up to seven months in a city for the test, results show that resident activity rules mining can be effectively carried out with the use of mobile phone positioning data. © Sila Science. All Rights Reserved.

引用

页码：7675 / 7682