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CIKM
2003
Springer
15 years 4 months ago
Dimensionality reduction using magnitude and shape approximations
High dimensional data sets are encountered in many modern database applications. The usual approach is to construct a summary of the data set through a lossy compression technique...
Ümit Y. Ogras, Hakan Ferhatosmanoglu
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
15 years 11 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...
GFKL
2007
Springer
180views Data Mining» more  GFKL 2007»
15 years 5 months ago
Content-based Dimensionality Reduction for Recommender Systems
Recommender Systems are gaining widespread acceptance in e-commerce applications to confront the information overload problem. Collaborative Filtering (CF) is a successful recommen...
Panagiotis Symeonidis
CIKM
2000
Springer
15 years 4 months ago
Dimensionality Reduction and Similarity Computation by Inner Product Approximations
—As databases increasingly integrate different types of information such as multimedia, spatial, time-series, and scientific data, it becomes necessary to support efficient retri...
Ömer Egecioglu, Hakan Ferhatosmanoglu
ECCV
2010
Springer
15 years 4 months ago
Fast Covariance Computation and Dimensionality Reduction for Sub-Window Features in Images
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...