TY - GEN
T1 - A Bayesian framework for individual exposure estimation on uncertain paths
AU - Horak, Matthew
AU - Bae, Wan D.
AU - Alkobaisi, Shayma
AU - Kim, Sehjeong
AU - Meyers, Wade
N1 - Funding Information:
This material is based upon works supported in part by the Information and Communication Technology Fund of the United Arab Emirates under award number 21T042 and in part by Hanyang University under award number 2016–473.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Current map matching and path reconstruction algorithms exhibit high success rates on dense data.We present a framework for estimating path selection probabilities from extremely sparse GPS data for the purpose of estimating a “measurement of interest” that varies with path and travel time. This work is motivated by limitations involved in applications such as environmental exposure modeling for medical patients. Our contributions are two-fold; first we propose a general Bayesian framework for path selection estimation that is applicable at both population and individual levels, and second, we provide extensive experiments on real and synthetic data that demonstrate the accuracy and robustness of the proposed algorithm and model.
AB - Current map matching and path reconstruction algorithms exhibit high success rates on dense data.We present a framework for estimating path selection probabilities from extremely sparse GPS data for the purpose of estimating a “measurement of interest” that varies with path and travel time. This work is motivated by limitations involved in applications such as environmental exposure modeling for medical patients. Our contributions are two-fold; first we propose a general Bayesian framework for path selection estimation that is applicable at both population and individual levels, and second, we provide extensive experiments on real and synthetic data that demonstrate the accuracy and robustness of the proposed algorithm and model.
KW - Bayesian estimation
KW - Exposome
KW - Path selection probability
UR - http://www.scopus.com/inward/record.url?scp=85018898839&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-55998-8_6
DO - 10.1007/978-3-319-55998-8_6
M3 - Conference contribution
AN - SCOPUS:85018898839
SN - 9783319559971
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 83
EP - 99
BT - Web and Wireless Geographical Information Systems - 15th International Symposium, W2GIS 2017, Proceedings
A2 - Wang, Tianzhen
A2 - Li, Xiang
A2 - Brosset, David
A2 - Claramunt, Christophe
PB - Springer Verlag
T2 - 15th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2017
Y2 - 8 May 2017 through 9 May 2017
ER -