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    SDM
    2010
    SIAM
    183views Data Mining» more  SDM 2010»
    GraSS: Graph Structure Summarization
    15 years 5 months ago
    GraSS: Graph Structure Summarization
    Download  www.cs.bu.edu
    Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...
    Kristen LeFevre, Evimaria Terzi
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    129
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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
    15 years 5 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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    140
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    SDM
    2008
    SIAM
    177views Data Mining» more  SDM 2008»
    Roughly Balanced Bagging for Imbalanced Data
    15 years 5 months ago
    Roughly Balanced Bagging for Imbalanced Data
    Download  siam.org
    Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
    Shohei Hido, Hisashi Kashima
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    112
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    IADIS
    2008
    98views Internet Technology» more  IADIS 2008»
    An E-Learning System To Prepare Negotiations
    15 years 5 months ago
    An E-Learning System To Prepare Negotiations
    Download  www.iadis.net
    The goal of this article is to propose an environment for negotiation e-learning courses using a workflow approach to help learners to prepare the negotiation. This environment is...
    Sérgio Assis Rodrigues, Yann Duzert, Jano M...
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    126
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    ISNN
    2007
    Springer
    118views Neural Networks» more  ISNN 2007»
    A Hierarchical Self-organizing Associative Memory for Machine Learning
    15 years 9 months ago
    A Hierarchical Self-organizing Associative Memory for Machine Learning
    Download  www.ent.ohiou.edu
    This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
    Janusz A. Starzyk, Haibo He, Yue Li
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