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» Graph Mining based on a Data Partitioning Approach
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ICDM
2006
IEEE
147views Data Mining» more  ICDM 2006»
15 years 6 months ago
Adaptive Parallel Graph Mining for CMP Architectures
Mining graph data is an increasingly popular challenge, which has practical applications in many areas, including molecular substructure discovery, web link analysis, fraud detect...
Gregory Buehrer, Srinivasan Parthasarathy, Yen-Kua...
PKDD
2004
Springer
147views Data Mining» more  PKDD 2004»
15 years 5 months ago
Using a Hash-Based Method for Apriori-Based Graph Mining
The problem of discovering frequent subgraphs of graph data can be solved by constructing a candidate set of subgraphs first, and then, identifying within this candidate set those...
Phu Chien Nguyen, Takashi Washio, Kouzou Ohara, Hi...
CGF
1999
125views more  CGF 1999»
15 years 1 days ago
Partitioning and Handling Massive Models for Interactive Collision Detection
We describe an approach for interactive collision detection and proximity computations on massive models composed of millions of geometric primitives. We address issues related to...
Andy Wilson, Eric Larsen, Dinesh Manocha, Ming C. ...
IPPS
2006
IEEE
15 years 6 months ago
Tree partition based parallel frequent pattern mining on shared memory systems
In this paper, we present a tree-partition algorithm for parallel mining of frequent patterns. Our work is based on FP-Growth algorithm, which is constituted of tree-building stag...
Dehao Chen, Chunrong Lai, Wei Hu, Wenguang Chen, Y...
114
Voted
KDD
2008
ACM
192views Data Mining» more  KDD 2008»
16 years 24 days ago
Partial least squares regression for graph mining
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...
Hiroto Saigo, Koji Tsuda, Nicole Krämer