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» Cluster Analysis of High-Dimensional Data: A Case Study
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IEEECIT
2005
IEEE
14 years 1 months ago
Case Study: Distance-Based Image Retrieval in the MoBIoS DBMS
Similarity search leveraging distance-based index structures is increasingly being used for complex data types. It has been shown that for high dimensional uniform vectors with si...
Rui Mao, Wenguo Liu, Daniel P. Miranker, Qasim Iqb...
ICDE
2003
IEEE
193views Database» more  ICDE 2003»
14 years 9 months ago
An Adaptive and Efficient Dimensionality Reduction Algorithm for High-Dimensional Indexing
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
Hui Jin, Beng Chin Ooi, Heng Tao Shen, Cui Yu, Aoy...
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
14 years 8 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
BMCBI
2006
164views more  BMCBI 2006»
13 years 7 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
INFOVIS
2003
IEEE
14 years 25 days ago
Interactive Hierarchical Dimension Ordering, Spacing and Filtering for Exploration of High Dimensional Datasets
Large numbers of dimensions not only cause clutter in multidimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension manage...
Jing Yang, Wei Peng, Matthew O. Ward, Elke A. Rund...