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Volumn , Issue , 2005, Pages 275-284

Prediction, expectation, and surprise: Methods, designs, and study of a deployed traffic forecasting service

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; TRAFFIC CONTROL;

EID: 70350579633     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (76)

References (11)
  • 1
    • 0002109327 scopus 로고    scopus 로고
    • Detecting change in categorical data: Mining contrast sets
    • Bay, S.D., & Pazzani, M.J. (1999). Detecting Change in Categorical Data: Mining Contrast Sets. Knowledge Discovery and Data Mining, pp. 302-499.
    • (1999) Knowledge Discovery and Data Mining , pp. 302-499
    • Bay, S.D.1    Pazzani, M.J.2
  • 2
    • 0002248815 scopus 로고    scopus 로고
    • A Bayesian approach to learning Bayesian networks with local structure
    • Chickering, D. M., Heckerman, D., & Meek, C. (1997). A Bayesian approach to learning Bayesian networks with local structure. Proceedings of UAI 97, 80-89.
    • (1997) Proceedings of UAI 97 , pp. 80-89
    • Chickering, D.M.1    Heckerman, D.2    Meek, C.3
  • 3
    • 0002594891 scopus 로고
    • Learning bayesian networks: A unification for discrete and gaussian domains
    • Heckerman, D. & Geiger, D. (1995). Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains. Proceedings of UAI 95, pp. 274-284.
    • (1995) Proceedings of UAI 95 , pp. 274-284
    • Heckerman, D.1    Geiger, D.2
  • 4
    • 0001873588 scopus 로고
    • Display of information for time-critical decision making
    • Horvitz, E., & Barry, M. (1995) Display of Information for Time-Critical Decision Making. Proceedings UAI 95, pp. 296-305.
    • (1995) Proceedings UAI 95 , pp. 296-305
    • Horvitz, E.1    Barry, M.2
  • 5
  • 7
    • 78651414408 scopus 로고    scopus 로고
    • Continuous time bayesian networks for inferring users' presence and activities with extensions for modeling and evaluation
    • December
    • Nodelman, U. & Horvitz, E. Continuous Time Bayesian Networks for Inferring Users' Presence and Activities with Extensions for Modeling and Evaluation, Microsoft Research Technical Report MSR-TR-2003-97, December 2003.
    • (2003) Microsoft Research Technical Report MSR-TR-2003-97
    • Nodelman, U.1    Horvitz, E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.