Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50010

Utilizing Geospatial Information in Cellular Data Usage for Key Location Prediction

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Title:Utilizing Geospatial Information in Cellular Data Usage for Key Location Prediction
Authors:Yu, Yinan
Ma, Baojun
Chen, Hailiang
Yen, Benjamin
Keywords:Decision Support for Smart Cities
cellular data usage, geospatial information, home and workplace, precision marketing, kernel density estimation
Date Issued:03 Jan 2018
Abstract:Previous research on the identification of key locations (e.g., home and workplace) for a user largely relies on call detail records (CDRs). Recently, cellular data usage (i.e., mobile internet) is growing rapidly and offers fine-grained insights into various human behavior patterns. In this study, we introduce a novel dataset containing both voice and mobile data usage records of mobile users. We then construct a new feature based on the geospatial distribution of cell towers connected by mobile users and employ bivariate kernel density estimation to help predict users’ key locations. The evaluation results suggest that augmented features based on both voice and mobile data usage improve the prediction precision and recall.
Pages/Duration:8 pages
URI/DOI:http://hdl.handle.net/10125/50010
ISBN:978-0-9981331-1-9
DOI:10.24251/HICSS.2018.123
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Decision Support for Smart Cities


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