An integrated K-means - Laplacian cluster ensemble approach for document datasets.
Sen XuKung-Sik ChanJun GaoXiufang XuXianfeng LiXiaopeng HuaJing AnPublished in: Neurocomputing (2016)
Keyphrases
- k means
- clustering approaches
- clustering algorithm
- document clustering
- data clustering
- hierarchical clustering
- cluster analysis
- unsupervised clustering
- clustering quality
- cluster centers
- text clustering
- initial cluster centers
- document clusters
- clustering method
- clustering framework
- information retrieval systems
- constrained clustering
- agglomerative hierarchical clustering
- database
- rough k means
- information retrieval
- self organizing maps
- text documents
- hierarchical agglomerative clustering
- document collections
- cluster membership
- document images
- retrieval systems
- subspace clustering
- benchmark datasets
- content similarity
- fuzzy c means
- document corpus
- clustering solutions
- keywords
- high dimensional datasets
- variable weighting
- spectral clustering
- hierarchical clustering algorithm
- fuzzy clustering
- cluster centroids
- semi supervised clustering
- document set
- document retrieval
- edge detection
- data points
- feature space
- feature selection
- data sets