Enriching Non-negative Matrix Factorization with Contextual Embeddings for Recommender Systems.
Zafran KhanNaima IltafHammad AfzalHaider AbbasPublished in: Neurocomputing (2020)
Keyphrases
- negative matrix factorization
- recommender systems
- matrix factorization
- collaborative filtering
- latent semantic space
- nonnegative matrix factorization
- contextual information
- document clustering
- low dimensional
- vector space
- principal component analysis
- sparse representation
- tensor factorization
- low rank
- user preferences
- constrained least squares
- user context
- manifold learning
- user profiles
- data sets
- dimensionality reduction
- implicit feedback
- probabilistic latent semantic analysis
- spectral clustering
- recommendation systems
- object recognition
- missing data
- multiscale