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Volumn 9, Issue 6, 2013, Pages 784-797

Where to go from here? Mobility prediction from instantaneous information

Author keywords

Artificial Neural Networks; Dynamical Bayesian Network; Gradient Boosted Decision Trees; Machine learning; Mobility prediction; Probabilistic Graphical Models

Indexed keywords

BAYESIAN NETWORKS; COMPUTER PROGRAMMING; DECISION TREES; LEARNING SYSTEMS; NEURAL NETWORKS;

EID: 84889092780     PISSN: 15741192     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pmcj.2013.07.006     Document Type: Conference Paper
Times cited : (38)

References (18)
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    • Friedman, J.H.1
  • 11
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    • Understanding individual human mobility patterns
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    • Gonzalez, M.C.1    Hidalgo, C.A.2    Barabási, A.-L.3
  • 12
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    • Modelling the scaling properties of human mobility
    • C. Song, T. Koren, P. Wang, and A.-L. Barabási Modelling the scaling properties of human mobility Nature Physics 6 2010 818 823
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    • Using GPS to learn significant locations and predict movement across multiple users
    • D. Ashbrook, and T. Starner Using GPS to learn significant locations and predict movement across multiple users Personal and Ubiquitous Computing 7 2003 275 286
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    • Scellato, S.1    Musolesi, M.2    Mascolo, C.3    Latora, V.4    Campbell, A.T.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.