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    KDD
    2008
    ACM
    147views Data Mining» more  KDD 2008»
    Extracting shared subspace for multi-label classification
    14 years 10 months ago
    Extracting shared subspace for multi-label classification
    Download  www.public.asu.edu
    Multi-label problems arise in various domains such as multitopic document categorization and protein function prediction. One natural way to deal with such problems is to construc...
    Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye
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    KDD
    2008
    ACM
    259views Data Mining» more  KDD 2008»
    Using ghost edges for classification in sparsely labeled networks
    14 years 10 months ago
    Using ghost edges for classification in sparsely labeled networks
    Download  reality.media.mit.edu
    We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
    Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
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    KDD
    2008
    ACM
    164views Data Mining» more  KDD 2008»
    Microscopic evolution of social networks
    14 years 10 months ago
    Microscopic evolution of social networks
    Download  www.cs.cmu.edu
    We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at ...
    Jure Leskovec, Lars Backstrom, Ravi Kumar, Andrew ...
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    KDD
    2008
    ACM
    119views Data Mining» more  KDD 2008»
    SAIL: summation-based incremental learning for information-theoretic clustering
    14 years 10 months ago
    SAIL: summation-based incremental learning for information-theoretic clustering
    Download  datamining.rutgers.edu
    Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
    Junjie Wu, Hui Xiong, Jian Chen
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    KDD
    2008
    ACM
    217views Data Mining» more  KDD 2008»
    Stream prediction using a generative model based on frequent episodes in event sequences
    14 years 10 months ago
    Stream prediction using a generative model based on frequent episodes in event sequences
    Download  research.microsoft.com
    This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
    Srivatsan Laxman, Vikram Tankasali, Ryen W. White
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