 Analysis of behavioral differentiation in smart cities based on mobile users’ usage detail record dataXianlong Zhao, Xianze Xu, He Nai, Chen Zhou, Zhiyi Hu, Yi Zhang and Hao Jiang International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 4, 1550147718770087 Abstract: The expansion of big data has played an important role in the feasibility of the smart city initiative. The massive amounts of data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources. Usage detail records not only include plentiful spatial–temporal information, but also describe users’ activities in content space and time. They have three dimensions of information, which makes them favorable for the research of human behavior dynamics. To support smart cities, we collected usage detail records containing three dimensions of information from individuals and analyzed the relationship between them to get modes of users’ behavior. In this article, we propose a method to discover the needed content for users and a way to provide these data to them. The result shows that two of these three dimensions have an invisible association. New behavioral patterns that we discovered from usage detail records can be derived for configuring resources reasonably and supporting creation of smart cities. Keywords: Usage detail record data; mobile user behavior analysis; pattern mining (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:4:p:1550147718770087 Access Statistics for this article More articles in International Journal of Distributed Sensor Networks |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.