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» Clustering Improves the Exploration of Graph Mining Results
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INCDM
2010
Springer
172views Data Mining» more  INCDM 2010»
14 years 10 months ago
Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
Many real world systems can be modeled as networks or graphs. Clustering algorithms that help us to organize and understand these networks are usually referred to as, graph based c...
Faraz Zaidi, Daniel Archambault, Guy Melanç...
ICDE
2006
IEEE
222views Database» more  ICDE 2006»
16 years 1 months ago
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
Jianyong Wang, Zhiping Zeng, Lizhu Zhou
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
15 years 5 months ago
On Feature Selection through Clustering
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the m...
Richard Butterworth, Gregory Piatetsky-Shapiro, Da...
IASSE
2004
15 years 1 months ago
A Model for Multi-relational Data Mining on Demand Forecasting
Accurate demand forecasting remains difficult and challenging in today's competitive and dynamic business environment, but even a little improvement in demand prediction may ...
Qin Ding, Bhavin Parikh
CIKM
2010
Springer
14 years 10 months ago
SHRINK: a structural clustering algorithm for detecting hierarchical communities in networks
Community detection is an important task for mining the structure and function of complex networks. Generally, there are several different kinds of nodes in a network which are c...
Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, ...