Utilizing Geospatial Information in Cellular Data Usage for Key Location Prediction

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationPROCEEDINGS OF THE 51ST ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS)
PublisherHICSS
Pages981-988
ISBN (Electronic)978-0-9981331-1-9
Publication statusPublished - 2018

Conference

Title51st Annual Hawaii International Conference on System Sciences (HICSS)
Period2 - 6 January 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.

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Citation Format(s)

Utilizing Geospatial Information in Cellular Data Usage for Key Location Prediction. / Yu, Yinan; Ma, Baojun; Chen, Hailiang; Yen, Benjamin.

PROCEEDINGS OF THE 51ST ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS). HICSS, 2018. p. 981-988.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review