Mining and clustering mobility evolution patterns from social media for urban informatics

Mining and clustering mobility evolution patterns from social media for urban informatics

In this paper, given a set of check-in data, we aim at discovering representative daily movement behavior of users in a city. For example, daily movement behavior on a weekday may show users moving from one to another spatial region associated with time information. Since check-in data contain both...

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Bibliographic Details
Main Authors: CHEN, Chien-Cheng, CHIANG, Meng-Fen, PENG, Wen-Chih
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
Data mining
Mobility pattern
Pattern clustering
Urban planning
Numerical Analysis and Scientific Computing
Social Media
Urban Studies and Planning
Online Access:https://ink.library.smu.edu.sg/sis_research/3631
https://ink.library.smu.edu.sg/context/sis_research/article/4633/viewcontent/Mining_and_clustering_mobility.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/3631
https://ink.library.smu.edu.sg/context/sis_research/article/4633/viewcontent/Mining_and_clustering_mobility.pdf

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