Block based Singular Value Decomposition approach to matrix factorization for recommender systems.
Prasad BhavanaVikas KumarVineet PadmanabhanPublished in: CoRR (2019)
Keyphrases
- matrix factorization
- singular value decomposition
- recommender systems
- collaborative filtering
- low rank
- singular values
- low rank matrix
- least squares
- cold start problem
- factor analysis
- data matrix
- negative matrix factorization
- dimensionality reduction
- data sparsity
- principal component analysis
- latent semantic indexing
- nonnegative matrix factorization
- linear algebra
- factorization method
- probabilistic matrix factorization
- latent semantic analysis
- tensor factorization
- implicit feedback
- factorization methods
- low rank approximation
- item recommendation
- stochastic gradient descent
- latent factor models
- information retrieval
- latent factors
- matrix completion
- measurement matrix