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AUSAI
2009
Springer
13 years 11 months ago
A Graph Distance Based Structural Clustering Approach for Networks
In the era of information explosion, structured data emerge on a large scale. As a description of structured data, network has drawn attention of researchers in many subjects. Netw...
Xin Su, Chunping Li
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
13 years 2 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
CMOT
2004
141views more  CMOT 2004»
13 years 4 months ago
Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs
We describe a methodology to examine bipartite relational data structures as exemplified in networks of corporate interlocking. These structures can be represented as bipartite gr...
Garry Robins, Malcolm Alexander
EDBT
2009
ACM
241views Database» more  EDBT 2009»
13 years 11 months ago
GADDI: distance index based subgraph matching in biological networks
Currently, a huge amount of biological data can be naturally represented by graphs, e.g., protein interaction networks, gene regulatory networks, etc. The need for indexing large ...
Shijie Zhang, Shirong Li, Jiong Yang
KDD
2004
ACM
137views Data Mining» more  KDD 2004»
13 years 10 months ago
Mining scale-free networks using geodesic clustering
Many real-world graphs have been shown to be scale-free— vertex degrees follow power law distributions, vertices tend to cluster, and the average length of all shortest paths is...
Andrew Y. Wu, Michael Garland, Jiawei Han