Document clustering method using dimension reduction and support vector clustering to overcome sparseness.
Sunghae JunSang-Sung ParkDong-Sik JangPublished in: Expert Syst. Appl. (2014)
Keyphrases
- clustering method
- dimension reduction
- cluster analysis
- support vector clustering
- document clustering
- clustering algorithm
- principal component analysis
- high dimensional problems
- high dimensional
- feature extraction
- singular value decomposition
- k means
- linear discriminant analysis
- fuzzy c means
- low dimensional
- hierarchical clustering
- manifold learning
- information retrieval
- subspace clustering
- random projections
- text clustering
- high dimensional data
- spectral clustering
- feature selection
- affinity propagation
- document collections
- clustering framework
- similarity measure
- similarity matrix
- feature space
- clustering result
- clustering analysis
- dimensionality reduction
- text documents
- unsupervised learning
- data clustering
- high dimensionality
- machine learning
- qr decomposition
- object recognition
- data mining techniques