Content-based Dimensionality Reduction for Recommender Systems.
Panagiotis SymeonidisPublished in: GfKl (2007)
Keyphrases
- recommender systems
- dimensionality reduction
- information filtering
- content based filtering
- collaborative filtering
- news recommendation
- image retrieval
- principal component analysis
- music recommendation
- high dimensional
- pattern recognition
- feature extraction
- data representation
- feature space
- high dimensional data
- low dimensional
- user preferences
- high dimensionality
- user profiles
- cold start problem
- data points
- manifold learning
- user modeling
- pattern recognition and machine learning
- information overload
- linear discriminant analysis
- principal components
- relevance feedback
- nonlinear dimensionality reduction
- structure preserving
- matrix factorization
- user model
- user feedback
- linear dimensionality reduction
- locally linear embedding
- user profiling
- cold start
- compound critiques
- multimedia
- feature selection
- trust aware
- collaborative filtering recommender systems
- machine learning
- product recommendation
- data sparsity
- dimensionality reduction methods
- personalized recommendation
- random projections
- nearest neighbor
- knn
- image processing
- computer vision