HOS-Miner: A System for Detecting Outlying Subspaces of High-dimensional Data.
Ji ZhangMeng LouTok Wang LingHai H. WangPublished in: VLDB (2004)
Keyphrases
- high dimensional data
- dimensionality reduction
- high dimensional
- low dimensional
- nearest neighbor
- high dimensionality
- high dimensions
- original data
- similarity search
- data sets
- data points
- subspace clustering
- dimension reduction
- data analysis
- input space
- high dimensional datasets
- low rank
- clustering high dimensional data
- lower dimensional
- high dimensional spaces
- linear discriminant analysis
- sparse representation
- input data
- dimensional data
- high dimensional data sets
- manifold learning
- missing values
- text data
- nonlinear dimensionality reduction
- neural network
- pattern recognition
- learning algorithm