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KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 8 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
MICRO
2009
IEEE
132views Hardware» more  MICRO 2009»
14 years 2 months ago
Finding concurrency bugs with context-aware communication graphs
Incorrect thread synchronization often leads to concurrency bugs that manifest nondeterministically and are difficult to detect and fix. Past work on detecting concurrency bugs ...
Brandon Lucia, Luis Ceze
SIGMOD
2010
ACM
196views Database» more  SIGMOD 2010»
13 years 8 months ago
GAIA: graph classification using evolutionary computation
Discriminative subgraphs are widely used to define the feature space for graph classification in large graph databases. Several scalable approaches have been proposed to mine disc...
Ning Jin, Calvin Young, Wei Wang
CIKM
2010
Springer
13 years 6 months ago
Fast and accurate estimation of shortest paths in large graphs
Computing shortest paths between two given nodes is a fundamental operation over graphs, but known to be nontrivial over large disk-resident instances of graph data. While a numbe...
Andrey Gubichev, Srikanta J. Bedathur, Stephan Seu...
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 6 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu