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    DMIN
    2006
    122views Data Mining» more  DMIN 2006»
    Clustering of Bi-Dimensional and Heterogeneous Time Series: Application to Social Sciences Data
    14 years 1 months ago
    Clustering of Bi-Dimensional and Heterogeneous Time Series: Application to Social Sciences Data
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    We present an application of bi-dimensional and heterogeneous time series clustering in order to resolve a Social Sciences issue. The dataset is the result of a survey involving mo...
    Rémi Gaudin, Sylvaine Barbier, Nicolas Nico...
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    DMIN
    2006
    138views Data Mining» more  DMIN 2006»
    Financial Time Series Segmentation based on Specialized Binary Tree Representation
    14 years 1 months ago
    Financial Time Series Segmentation based on Specialized Binary Tree Representation
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    Segmentation is one of the fundamental components in time series data mining. One of the uses of the time series segmentation is trend analysis - to segment the time series into pr...
    Tak-Chung Fu, Fu-Lai Chung, Chak-man Ng
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    DBA
    2006
    236views Database» more  DBA 2006»
    Quantizing Time Series for Efficient Subsequence Matching
    14 years 1 months ago
    Quantizing Time Series for Efficient Subsequence Matching
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    Indexing time series data is an interesting problem that has attracted much interest in the research community for the last decade. Traditional indexing methods organize the data ...
    Inés Fernando Vega López, Bongki Moo...
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    SDM
    2007
    SIAM
    171views Data Mining» more  SDM 2007»
    A Better Alternative to Piecewise Linear Time Series Segmentation
    14 years 1 months ago
    A Better Alternative to Piecewise Linear Time Series Segmentation
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    Time series are difficult to monitor, summarize and predict. Segmentation organizes time series into few intervals having uniform characteristics (flatness, linearity, modality,...
    Daniel Lemire
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    IJCAI
    2007
    184views Artificial Intelligence» more  IJCAI 2007»
    All Common Subsequences
    14 years 1 months ago
    All Common Subsequences
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    Time series data abounds in real world problems. Measuring the similarity of time series is a key to solving these problems. One state of the art measure is the longest common sub...
    Hui Wang
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    ICONIP
    2008
    161views Information Technology» more  ICONIP 2008»
    Time Series Analysis for Long Term Prediction of Human Movement Trajectories
    14 years 1 months ago
    Time Series Analysis for Long Term Prediction of Human Movement Trajectories
    Download  www.tu-ilmenau.de
    This paper's intention is to adapt prediction algorithms well known in the field of time series analysis to problems being faced in the field of mobile robotics and Human-Robo...
    Sven Hellbach, Julian Eggert, Edgar Körner, H...
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    ICONIP
    2008
    105views Information Technology» more  ICONIP 2008»
    An Exemplar-Based Statistical Model for the Dynamics of Neural Synchrony
    14 years 1 months ago
    An Exemplar-Based Statistical Model for the Dynamics of Neural Synchrony
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    Abstract. A method is proposed to determine the similarity of a collection of time series. As a first step, one extracts events from the time series, in other words, one converts e...
    Justin Dauwels, François B. Vialatte, Theop...
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    IADIS
    2008
    173views Internet Technology» more  IADIS 2008»
    Data Mining In Non-Stationary Multidimensional Time Series Using A Rule Similarity Measure
    14 years 1 months ago
    Data Mining In Non-Stationary Multidimensional Time Series Using A Rule Similarity Measure
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    Time series analysis is a wide area of knowledge that studies processes in their evolution. The classical research in the area tends to find global laws underlying the behaviour o...
    Nikolay V. Filipenkov
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    SDM
    2010
    SIAM
    156views Data Mining» more  SDM 2010»
    Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
    14 years 1 months ago
    Unsupervised Discovery of Abnormal Activity Occurrences in Multi-dimensional Time Series, with Applications in Wearable Systems
    Download  cs.ucla.edu
    We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
    Alireza Vahdatpour, Majid Sarrafzadeh
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    EUSFLAT
    2007
    227views Fuzzy Logic» more  EUSFLAT 2007»
    Time Series Prediction by Perturbed Fuzzy Model
    14 years 1 months ago
    Time Series Prediction by Perturbed Fuzzy Model
    Download  www.eusflat.org
    This paper presents a fuzzy system approach to the prediction of nonlinear time series and dynamical systems based on a fuzzy model that includes its derivative information. The u...
    Paulo Salgado, Getúlio Igrejas, Fernando Go...
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