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Volumn , Issue , 2013, Pages 1219-1227

Anomalous event detection on large-scale GPS data from mobile phones using hidden markov model and cloud platform

Author keywords

Anomaly detection; GPS trajectories; Hadoop; Hidden markov; Mobile phone

Indexed keywords

ANOMALY DETECTION; GPS TRAJECTORIES; HADOOP; HIDDEN MARKOV; LARGE-SCALE DATUM; MOBILE-PHONE USERS; MOVEMENT OF PEOPLES; NATURAL DISASTERS;

EID: 84885199308     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2494091.2497352     Document Type: Conference Paper
Times cited : (37)

References (14)
  • 1
    • 84875644869 scopus 로고    scopus 로고
    • Using GPS to learn significant locations and predict movement across multiple users
    • 275-286
    • Ashbrook, D., Starner, T. Using GPS to learn significant locations and predict movement across multiple users. Personal and Ubiquitous Computing (2003), 7(5), 275-286.
    • (2003) Personal and Ubiquitous Computing , vol.7 , Issue.5
    • Ashbrook, D.1    Starner, T.2
  • 2
    • 34547410460 scopus 로고    scopus 로고
    • Discovering personally meaningful places: An interactive clustering approach
    • C. Zhou, et al. Discovering Personally Meaningful Places: An Interactive Clustering Approach. In ACM Trans. on Information Systems (2007), vol. 25(3).
    • (2007) ACM Trans. on Information Systems , vol.25 , Issue.3
    • Zhou, C.1
  • 3
    • 33947594196 scopus 로고    scopus 로고
    • Building personal map from GPS data
    • Springer Press
    • Liao, L., et al. Building Personal Map from GPS Data. In proceedings of IJCAI MOO05, Springer Press (2005), 249-265.
    • (2005) Proceedings of IJCAI MOO05 , pp. 249-265
    • Liao, L.1
  • 7
    • 78149351008 scopus 로고    scopus 로고
    • Clustering of time series subsequences is meaningless: Implications for previous and future research
    • Keogh, E., Lin, J., and Truppel, W. Clustering of time series subsequences is meaningless: implications for previous and future research. Third IEEE International Conference on Data Mining, (2003), . 115-122.
    • (2003) Third IEEE International Conference on Data Mining , pp. 115-122
    • Keogh, E.1    Lin, J.2    Truppel, W.3
  • 11
  • 12
    • 84875152530 scopus 로고    scopus 로고
    • Hive Project: http://hive.apache.org/.
    • Hive Project


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.