A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques.
Mehrbakhsh NilashiOthman IbrahimKaramollah BagherifardPublished in: Expert Syst. Appl. (2018)
Keyphrases
- collaborative filtering
- recommender systems
- dimensionality reduction
- matrix factorization
- data sparsity
- cold start problem
- principal component analysis
- low dimensional
- data representation
- domain ontology
- semantic web
- information filtering
- knowledge representation
- cold start
- domain knowledge
- recommendation quality
- high dimensional data
- personalized recommendation
- recommendation systems
- data points
- online dating
- high dimensionality
- domain specific
- high dimensional
- user preferences
- user interests
- product recommendation
- dimensionality reduction methods
- manifold learning
- semantic information
- user profiles
- netflix prize
- pattern recognition
- probabilistic matrix factorization
- information overload
- structure preserving
- feature selection
- making recommendations
- content based filtering
- deal with information overload
- spreading activation
- semantic annotation
- feature space
- feature extraction
- knowledge base
- user ratings
- kernel learning
- pattern recognition and machine learning
- linear discriminant analysis