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» A Partition-Based Approach to Graph Mining
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PKDD
2010
Springer
235views Data Mining» more  PKDD 2010»
13 years 6 months ago
Online Structural Graph Clustering Using Frequent Subgraph Mining
The goal of graph clustering is to partition objects in a graph database into different clusters based on various criteria such as vertex connectivity, neighborhood similarity or t...
Madeleine Seeland, Tobias Girschick, Fabian Buchwa...
CORR
2011
Springer
199views Education» more  CORR 2011»
13 years 3 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...
FLAIRS
2006
13 years 10 months ago
Improving Modularity in Genetic Programming Using Graph-Based Data Mining
We propose to improve the efficiency of genetic programming, a method to automatically evolve computer programs. We use graph-based data mining to identify common aspects of highl...
Istvan Jonyer, Akiko Himes
KDD
2010
ACM
240views Data Mining» more  KDD 2010»
14 years 12 days ago
Diagnosing memory leaks using graph mining on heap dumps
Memory leaks are caused by software programs that prevent the reclamation of memory that is no longer in use. They can cause significant slowdowns, exhaustion of available storag...
Evan K. Maxwell, Godmar Back, Naren Ramakrishnan
SAC
2008
ACM
13 years 8 months ago
Mining fault-tolerant frequent patterns efficiently with powerful pruning
The mining of frequent patterns in databases has been studied for several years. However, the real-world data tends to be dirty and frequent pattern mining which extracts patterns...
Jhih-Jie Zeng, Guanling Lee, Chung-Chi Lee