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    146
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    PAKDD
    1999
    ACM
    99views Data Mining» more  PAKDD 1999»
    Efficient Graph-Based Algorithm for Discovering and Maintaining Knowledge in Large Databases
    15 years 10 months ago
    Efficient Graph-Based Algorithm for Discovering and Maintaining Knowledge in Large Databases
    Download  www.csie.ndhu.edu.tw
    K. L. Lee, Guanling Lee, Arbee L. P. Chen
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    143
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    KDD
    2010
    ACM
    271views Data Mining» more  KDD 2010»
    Parallel SimRank computation on large graphs with iterative aggregation
    15 years 4 months ago
    Parallel SimRank computation on large graphs with iterative aggregation
    Download  users.cis.fiu.edu
    Guoming He, Haijun Feng, Cuiping Li, Hong Chen
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    144
    Voted
    SDM
    2012
    SIAM
    284views Data Mining» more  SDM 2012»
    The Similarity Between Stochastic Kronecker and Chung-Lu Graph Models
    13 years 8 months ago
    The Similarity Between Stochastic Kronecker and Chung-Lu Graph Models
    Download  siam.omnibooksonline.com
    C. Seshadhri, Ali Pinar, Tamara G. Kolda
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    164
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    PAKDD
    2009
    ACM
    134views Data Mining» more  PAKDD 2009»
    On Link Privacy in Randomizing Social Networks.
    16 years 3 months ago
    On Link Privacy in Randomizing Social Networks.
    Download  www.sis.uncc.edu
    Many applications of social networks require relationship anonymity due to the sensitive, stigmatizing, or confidential nature of relationship. Recent work showed that the simple ...
    Xiaowei Ying, Xintao Wu
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    189
    Voted
    ICDM
    2009
    IEEE
    139views Data Mining» more  ICDM 2009»
    Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets
    15 years 4 months ago
    Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets
    Download  dblab.cs.nccu.edu.tw
    In this paper, we focus on a single graph whose vertices contain a set of quantitative attributes. Several networks can be naturally represented in this complex graph. An example i...
    Yuuki Miyoshi, Tomonobu Ozaki, Takenao Ohkawa
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