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» On the Performance of Ant-based Clustering
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DMIN
2006
151views Data Mining» more  DMIN 2006»
15 years 7 months ago
Rough Set Theory: Approach for Similarity Measure in Cluster Analysis
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
Shuchita Upadhyaya, Alka Arora, Rajni Jain
GLOBECOM
2007
IEEE
15 years 6 months ago
Connectivity, Energy and Mobility Driven Clustering Algorithm for Mobile Ad Hoc Networks
—In the context of mobile ad hoc networks (MANETs) routing, we propose a clustering algorithm called Connectivity, Energy and Mobility driven Clustering Algorithm (CEMCA). The ai...
Fatiha Djemili Tolba, Damien Magoni, Pascal Lorenz
PRL
2008
135views more  PRL 2008»
15 years 6 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
KDD
2007
ACM
220views Data Mining» more  KDD 2007»
16 years 6 months ago
SCAN: a structural clustering algorithm for networks
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
ISPASS
2006
IEEE
16 years 6 days ago
Comparing multinomial and k-means clustering for SimPoint
SimPoint is a technique used to pick what parts of the program’s execution to simulate in order to have a complete picture of execution. SimPoint uses data clustering algorithms...
Greg Hamerly, Erez Perelman, Brad Calder