Employing singular value decomposition and similarity criteria for alleviating cold start and sparse data in context-aware recommender systems.
Keyvan Vahidy RodpyshSeyed Javad MirabediniTouraj BanirostamPublished in: Electron. Commer. Res. (2023)
Keyphrases
- context aware
- singular value decomposition
- sparse data
- cold start
- recommender systems
- cold start problem
- collaborative filtering
- high dimensional
- contextual information
- dimensionality reduction
- least squares
- mobile devices
- implicit feedback
- dimension reduction
- matrix factorization
- user preferences
- principal component analysis
- data sparsity
- user context
- information overload
- recommendation algorithms
- personalized recommendation
- tag recommendation
- user feedback
- recommendation systems
- random projections
- user model
- user profiles
- user ratings
- semantic similarity
- data analysis
- user interests
- pattern recognition