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A probabilistic kernel method for human mobility prediction with smartphones · Study

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ArticleA probabilistic kernel method for human mobility prediction with smartphones

Trinh Minh Tri2014

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Articlegreen2014

A probabilistic kernel method for human mobility prediction with smartphones

Trinh Minh Tri · Olivier Dousse · Markus Miettinen · Daniel Gática-Pérez

66 citations·0/0 files stored·Pervasive and Mobile Computing

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Human Mobility and Location-Based Analysis Data Management and Algorithms Traffic Prediction and Management Techniques

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References

2010Limits of Predictability in Human Mobility 2003Using GPS to learn significant locations and predict movement across multiple users 2006Predestination: Inferring Destinations from Partial Trajectories 2012The Mobile Data Challenge: Big Data for Mobile Computing Research 2011Mining large-scale smartphone data for personality studies 2010Towards rich mobile phone datasets: Lausanne data collection campaign 2011NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems 2012Contextual conditional models for smartphone-based human mobility prediction

Cited by

2018How Big Data Fast Tracked Human Mobility Research and the Lessons for Animal Movement Ecology 2018A new procedure using network analysis and kernel density estimations to evaluate the effect of urban configurations on pedestrian mobility. The case study of Vitoria –Gasteiz 2017Human mobility in space from three modes of public transportation 2019Big Five personality traits predict daily spatial behavior: Evidence from smartphone data 2019On the accuracy and potential of Google Maps location history data to characterize individual mobility for air pollution health studies

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Details

Year2014

Typearticle

Published2014-09-16

VenuePervasive and Mobile Computing

ISSN-L1574-1192

Languageen

Citations66

Files0 public / 0

ShelfHuman Mobility and Location-Based Analysis

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doi10.1016/j.pmcj.2014.09.001

openalex_workW2139076288

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