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    SDM
    2009
    SIAM
    113views Data Mining» more  SDM 2009»
    Local Relevance Weighted Maximum Margin Criterion for Text Classification.
    14 years 8 months ago
    Local Relevance Weighted Maximum Margin Criterion for Text Classification.
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    Jie Zhou, Quanquan Gu
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    SDM
    2009
    SIAM
    144views Data Mining» more  SDM 2009»
    On Segment-Based Stream Modeling and Its Applications.
    14 years 8 months ago
    On Segment-Based Stream Modeling and Its Applications.
    Download  www.siam.org
    The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
    Charu C. Aggarwal
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    SDM
    2009
    SIAM
    114views Data Mining» more  SDM 2009»
    GAD: General Activity Detection for Fast Clustering on Large Data.
    14 years 8 months ago
    GAD: General Activity Detection for Fast Clustering on Large Data.
    Download  www.siam.org
    In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
    Jiawei Han, Liangliang Cao, Sangkyum Kim, Xin Jin,...
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    SDM
    2009
    SIAM
    161views Data Mining» more  SDM 2009»
    Feature Weighted SVMs Using Receiver Operating Characteristics.
    14 years 8 months ago
    Feature Weighted SVMs Using Receiver Operating Characteristics.
    Download  www.siam.org
    Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
    Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
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    SDM
    2009
    SIAM
    124views Data Mining» more  SDM 2009»
    Non-parametric Information-Theoretic Measures of One-Dimensional Distribution Functions from Continuous Time Series.
    14 years 8 months ago
    Non-parametric Information-Theoretic Measures of One-Dimensional Distribution Functions from Continuous Time Series.
    Download  siam.org
    We study non-parametric measures for the problem of comparing distributions, which arise in anomaly detection for continuous time series. Non-parametric measures take two distribu...
    Ali Dasdan, Paolo D'Alberto
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    SDM
    2009
    SIAM
    104views Data Mining» more  SDM 2009»
    On Randomness Measures for Social Networks.
    14 years 8 months ago
    On Randomness Measures for Social Networks.
    Download  www.siam.org
    Social networks tend to contain some amount of randomness and some amount of non-randomness. The amount of randomness versus non-randomness affects the properties of a social netw...
    Xiaowei Ying, Xintao Wu
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    SDM
    2009
    SIAM
    251views Data Mining» more  SDM 2009»
    High Performance Parallel/Distributed Biclustering Using Barycenter Heuristic.
    14 years 8 months ago
    High Performance Parallel/Distributed Biclustering Using Barycenter Heuristic.
    Download  www.siam.org
    Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and co...
    Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...
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    DAWAK
    2009
    Springer
    130views Information Technology» more  DAWAK 2009»
    Recommending Multidimensional Queries.
    14 years 8 months ago
    Recommending Multidimensional Queries.
    Download  www.info.univ-tours.fr
    Interactive analysis of datacube, in which a user navigates a cube by launching a sequence of queries is often tedious since the user may have no idea of what the forthcoming query...
    Arnaud Giacometti, Elsa Negre, Patrick Marcel
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    PAKDD
    2009
    ACM
    120views Data Mining» more  PAKDD 2009»
    Detecting Link Hijacking by Web Spammers.
    14 years 8 months ago
    Detecting Link Hijacking by Web Spammers.
    Download  www.tkl.iis.u-tokyo.ac.jp
    Abstract. Since current search engines employ link-based ranking algorithms as an important tool to decide a ranking of sites, Web spammers are making a significant effort to man...
    Masaru Kitsuregawa, Masashi Toyoda, Young-joo Chun...
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    PAKDD
    2009
    ACM
    170views Data Mining» more  PAKDD 2009»
    Discovering Periodic-Frequent Patterns in Transactional Databases.
    14 years 8 months ago
    Discovering Periodic-Frequent Patterns in Transactional Databases.
    Download  making.csie.ndhu.edu.tw
    Since mining frequent patterns from transactional databases involves an exponential mining space and generates a huge number of patterns, efficient discovery of user-interest-based...
    Byeong-Soo Jeong, Chowdhury Farhan Ahmed, Syed Kha...
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