Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases.
Eamonn J. KeoghKaushik ChakrabartiMichael J. PazzaniSharad MehrotraPublished in: Knowl. Inf. Syst. (2001)
Keyphrases
- dimensionality reduction
- high dimensional data
- principal component analysis
- similarity search
- high dimensional
- low dimensional
- pattern recognition
- feature extraction
- dimensionality reduction methods
- manifold learning
- random projections
- feature selection
- data representation
- feature space
- principal components analysis
- input space
- structure preserving
- data points
- euclidean distance
- linear discriminant analysis
- high dimensionality
- principal components
- preprocessing step
- singular value decomposition
- image processing
- pattern recognition and machine learning
- lower dimensional
- linear dimensionality reduction
- neural network
- dimension reduction
- kernel learning
- nonlinear dimensionality reduction
- intrinsic dimensionality
- graph embedding
- input data
- diffusion maps
- similarity measure
- databases
- supervised dimensionality reduction