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» Mining significant graph patterns by leap search
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SIGMOD
2008
ACM
144views Database» more  SIGMOD 2008»
14 years 4 months ago
Mining significant graph patterns by leap search
With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. ...
Xifeng Yan, Hong Cheng, Jiawei Han, Philip S. Yu
ICDE
2009
IEEE
290views Database» more  ICDE 2009»
14 years 6 months ago
GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases
Graphs are being increasingly used to model a wide range of scientific data. Such widespread usage of graphs has generated considerable interest in mining patterns from graph datab...
Sayan Ranu, Ambuj K. Singh
ICPADS
2006
IEEE
13 years 10 months ago
Parallel Leap: Large-Scale Maximal Pattern Mining in a Distributed Environment
When computationally feasible, mining extremely large databases produces tremendously large numbers of frequent patterns. In many cases, it is impractical to mine those datasets d...
Mohammad El-Hajj, Osmar R. Zaïane
KDD
2005
ACM
122views Data Mining» more  KDD 2005»
14 years 5 months ago
Pattern lattice traversal by selective jumps
Regardless of the frequent patterns to discover, either the full frequent patterns or the condensed ones, either closed or maximal, the strategy always includes the traversal of t...
Osmar R. Zaïane, Mohammad El-Hajj
KDD
2006
ACM
156views Data Mining» more  KDD 2006»
14 years 5 months ago
Discovering significant OPSM subspace clusters in massive gene expression data
Order-preserving submatrixes (OPSMs) have been accepted as a biologically meaningful subspace cluster model, capturing the general tendency of gene expressions across a subset of ...
Byron J. Gao, Obi L. Griffith, Martin Ester, Steve...