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» A New Indexing Method for High Dimensional Dataset
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CCGRID
2010
IEEE
13 years 8 months ago
High Performance Dimension Reduction and Visualization for Large High-Dimensional Data Analysis
Abstract--Large high dimension datasets are of growing importance in many fields and it is important to be able to visualize them for understanding the results of data mining appro...
Jong Youl Choi, Seung-Hee Bae, Xiaohong Qiu, Geoff...
DAWAK
2005
Springer
14 years 27 days ago
Nearest Neighbor Search on Vertically Partitioned High-Dimensional Data
Abstract. In this paper, we present a new approach to indexing multidimensional data that is particularly suitable for the efficient incremental processing of nearest neighbor quer...
Evangelos Dellis, Bernhard Seeger, Akrivi Vlachou
SSDBM
2003
IEEE
105views Database» more  SSDBM 2003»
14 years 19 days ago
Using Bitmap Index for Interactive Exploration of Large Datasets
Many scientific applications generate large spatiotemporal datasets. A common way of exploring these datasets is to identify and track regions of interest. Usually these regions ...
Kesheng Wu, Wendy S. Koegler, Jacqueline Chen, Ari...
AI
2006
Springer
13 years 11 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda
ICDM
2006
IEEE
132views Data Mining» more  ICDM 2006»
14 years 1 months ago
High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Hassan H. Malik, John R. Kender