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FLAIRS
2004
15 years 3 months ago
Adaptive K-Means Clustering
Clustering is used to organize data for efficient retrieval. One of the problems in clustering is the identification of clusters in given data. A popular technique for clustering ...
Sanjiv K. Bhatia
99
Voted
INFOVIS
2005
IEEE
15 years 7 months ago
Parallel Sets: Visual Analysis of Categorical Data
The discrete nature of categorical data makes it a particular challenge for visualization. Methods that work very well for continuous data are often hardly usable with categorical...
Fabian Bendix, Robert Kosara, Helwig Hauser
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
15 years 9 days ago
Using data mining techniques to address critical information exchange needs in disaster affected public-private networks
Crisis Management and Disaster Recovery have gained immense importance in the wake of recent man and nature inflicted calamities. A critical problem in a crisis situation is how t...
Li Zheng, Chao Shen, Liang Tang, Tao Li, Steven Lu...
350
Voted
ICDE
2003
IEEE
247views Database» more  ICDE 2003»
16 years 3 months ago
CLUSEQ: Efficient and Effective Sequence Clustering
Analyzing sequence data has become increasingly important recently in the area of biological sequences, text documents, web access logs, etc. In this paper, we investigate the pro...
Jiong Yang, Wei Wang 0010
GECCO
2008
Springer
171views Optimization» more  GECCO 2008»
15 years 3 months ago
Particle swarm clustering ensemble
Extracting natural groups of the unlabeled data is known as clustering. To improve the stability and robustness of the clustering outputs, clustering ensembles have emerged recent...
Abbas Ahmadi, Fakhri Karray, Mohamed Kamel