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» High Dimensional Similarity Joins: Algorithms and Performanc...
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BMCBI
2010
243views more  BMCBI 2010»
14 years 11 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
IEEECIT
2005
IEEE
15 years 5 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...
DAGM
2010
Springer
15 years 24 days ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
EWCBR
2006
Springer
15 years 3 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
16 years 2 days ago
Ensemble-index: a new approach to indexing large databases
The problem of similarity search (query-by-content) has attracted much research interest. It is a difficult problem because of the inherently high dimensionality of the data. The ...
Eamonn J. Keogh, Selina Chu, Michael J. Pazzani