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» On the Vulnerability of Large Graphs
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KDD
2005
ACM
157views Data Mining» more  KDD 2005»
16 years 7 months ago
A fast kernel-based multilevel algorithm for graph clustering
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
COMAD
2009
15 years 7 months ago
Graph Clustering for Keyword Search
Keyword search on data represented as graphs, is receiving lot of attention in recent years. Initial versions of keyword search systems assumed that the graph is memory resident. ...
Rose Catherine K., S. Sudarshan
BMCBI
2008
145views more  BMCBI 2008»
15 years 6 months ago
Directed acyclic graph kernels for structural RNA analysis
Background: Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel ...
Kengo Sato, Toutai Mituyama, Kiyoshi Asai, Yasubum...
CIKM
2009
Springer
16 years 1 months ago
A query language for analyzing networks
With more and more large networks becoming available, mining and querying such networks are increasingly important tasks which are not being supported by database models and query...
Anton Dries, Siegfried Nijssen, Luc De Raedt
CPHYSICS
2006
124views more  CPHYSICS 2006»
15 years 6 months ago
Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks
State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms s...
Cheng Zhang, Bhupesh Bansal, Paulo S. Branicio, Ra...