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IDEAS
1999
IEEE
123views Database» more  IDEAS 1999»
14 years 3 days ago
Improving OLAP Performance by Multidimensional Hierarchical Clustering
Data-warehousing applications cope with enormous data sets in the range of Gigabytes and Terabytes. Queries usually either select a very small set of this data or perform aggregat...
Volker Markl, Frank Ramsak, Rudolf Bayer
EUROPAR
2004
Springer
13 years 11 months ago
Efficient Parallel Hierarchical Clustering
Hierarchical agglomerative clustering (HAC) is a common clustering method that outputs a dendrogram showing all N levels of agglomerations where N is the number of objects in the d...
Manoranjan Dash, Simona Petrutiu, Peter Scheuerman...
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
14 years 8 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
PRL
2006
139views more  PRL 2006»
13 years 7 months ago
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...
KDD
2001
ACM
169views Data Mining» more  KDD 2001»
14 years 8 months ago
Hierarchical cluster analysis of SAGE data for cancer profiling
In this paper we present a method for clustering SAGE (Serial Analysis of Gene Expression) data to detect similarities and dissimilarities between different types of cancer on the...
Jörg Sander, Monica C. Sleumer, Raymond T. Ng