A fuzzy feature clustering with relevance feedback approach to content-based image retrieval.
Yo-Ping HuangTsun-Wei ChangChi-Zhan HuangPublished in: VECIMS (2003)
Keyphrases
- relevance feedback
- improve the retrieval accuracy
- feature importance
- low level visual features
- image retrieval
- retrieval accuracy
- clustering algorithm
- information retrieval systems
- query expansion
- fuzzy clustering
- user feedback
- low level features
- fuzzy logic
- fuzzy sets
- clustering method
- multiple features
- fuzzy c means clustering
- information retrieval
- k means
- active learning
- clustering analysis
- image search
- relevant documents
- membership functions
- retrieval model
- data clustering
- language model
- retrieval precision
- data points
- document clustering
- hierarchical clustering
- image features
- neural network
- metadata
- feature vectors
- pseudo relevance feedback
- retrieval process
- learning process
- fuzzy numbers
- image database
- unsupervised learning
- query refinement
- website
- feature set
- multimedia
- low level image features
- multimedia content
- fuzzy clustering algorithms
- cluster validity index
- document retrieval