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    FSKD
    2005
    Springer
    267views Fuzzy Logic» more  FSKD 2005»
    Preventing Meaningless Stock Time Series Pattern Discovery by Changing Perceptually Important Point Detection
    14 years 4 months ago
    Preventing Meaningless Stock Time Series Pattern Discovery by Changing Perceptually Important Point Detection
    Download  www.cse.ust.hk
    Discovery of interesting or frequently appearing time series patterns is one of the important tasks in various time series data mining applications. However, recent research critic...
    Tak-Chung Fu, Fu-Lai Chung, Robert W. P. Luk, Chak...
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    SDM
    2009
    SIAM
    343views Data Mining» more  SDM 2009»
    Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
    14 years 8 months ago
    Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation.
    Download  www.siam.org
    Change-point detection is the problem of discovering time points at which properties of time-series data change. This covers a broad range of real-world problems and has been acti...
    Masashi Sugiyama, Yoshinobu Kawahara
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    ICPR
    2008
    IEEE
    150views Computer Vision» more  ICPR 2008»
    A Mixed Markov model for change detection in aerial photos with large time differences
    14 years 5 months ago
    A Mixed Markov model for change detection in aerial photos with large time differences
    Download  figment.cse.usf.edu
    In the paper we propose a novel multi-layer Mixed Markov model for detecting relevant changes in registered aerial images taken with significant time differences. The introduced ...
    Csaba Benedek, Tamás Szirányi
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    ICSE
    2009
    IEEE-ACM
    131views Software Engineering» more  ICSE 2009»
    Improving quality, one process change at a time
    14 years 5 months ago
    Improving quality, one process change at a time
    Download  sillito.ca
    We report on one organization's experience making process changes in a suite of projects. The changes were motivated by clients’ requests for better time estimates, better ...
    Caryna Pinheiro, Frank Maurer, Jonathan Sillito
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    SDM
    2007
    SIAM
    198views Data Mining» more  SDM 2007»
    Learning from Time-Changing Data with Adaptive Windowing
    14 years 9 days ago
    Learning from Time-Changing Data with Adaptive Windowing
    Download  siam.org
    We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
    Albert Bifet, Ricard Gavaldà
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