Top-N Recommendation Using Low-Rank Matrix Completion and Spectral Clustering.
Qian WangQingmei ZhouWei ZhaoXuangou WuXun ShaoPublished in: IEICE Trans. Commun. (2020)
Keyphrases
- matrix completion
- spectral clustering
- low rank
- affinity matrix
- convex optimization
- linear combination
- low rank matrix approximation
- missing data
- eigendecomposition
- matrix factorization
- data clustering
- rank minimization
- singular value decomposition
- semi supervised
- pairwise
- low rank matrix
- norm minimization
- clustering method
- kernel matrix
- high order
- k means
- image segmentation
- high dimensional data
- trace norm
- graph laplacian
- normalized cut
- nonnegative matrix factorization
- clustering algorithm
- low rank approximation
- singular values
- semi supervised learning
- image processing
- feature selection
- data points
- data sets
- labeled data
- computer vision
- learning algorithm