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ICDE
2012
IEEE
227views Database» more  ICDE 2012»
11 years 7 months ago
Horizontal Reduction: Instance-Level Dimensionality Reduction for Similarity Search in Large Document Databases
—Dimensionality reduction is essential in text mining since the dimensionality of text documents could easily reach several tens of thousands. Most recent efforts on dimensionali...
Min-Soo Kim 0001, Kyu-Young Whang, Yang-Sae Moon
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
14 years 5 months ago
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...
ICDE
2002
IEEE
209views Database» more  ICDE 2002»
14 years 6 months ago
Geometric-Similarity Retrieval in Large Image Bases
We propose a novel approach to shape-based image retrieval that builds upon a similarity criterion which is based on the average point set distance. Compared to traditional techni...
Ioannis Fudos, Leonidas Palios, Evaggelia Pitoura
KDD
2001
ACM
203views Data Mining» more  KDD 2001»
14 years 5 months 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
SIGMOD
2006
ACM
125views Database» more  SIGMOD 2006»
14 years 5 months ago
A non-linear dimensionality-reduction technique for fast similarity search in large databases
To enable efficient similarity search in large databases, many indexing techniques use a linear transformation scheme to reduce dimensions and allow fast approximation. In this re...
Khanh Vu, Kien A. Hua, Hao Cheng, Sheau-Dong Lang