Similarity Measure Based on Low-Rank Approximation for Highly Scalable Recommender Systems.
Sepideh SeifzadehAli MiriPublished in: TrustCom/BigDataSE/ISPA (2) (2015)
Keyphrases
- highly scalable
- low rank approximation
- recommender systems
- singular value decomposition
- low rank matrix approximation
- low rank
- matrix factorization
- collaborative filtering
- spectral clustering
- subspace learning
- kernel matrix
- nonnegative matrix factorization
- adjacency matrix
- data dependent
- latent semantic indexing
- reconstruction error
- iterative algorithms
- dimensionality reduction
- pairwise
- least squares
- missing data
- clustering method