A Comparative Study: Classification Vs. Matrix Factorization for Therapeutics Recommendation.
Seda Polat ErdenizMichael SchrempfDiether KramerAlexander FelfernigPublished in: ISMIS (2022)
Keyphrases
- matrix factorization
- collaborative filtering
- recommender systems
- item recommendation
- data sparsity
- low rank
- factorization methods
- cold start problem
- text classification
- image classification
- latent factor models
- implicit feedback
- missing data
- factor analysis
- personalized recommendation
- negative matrix factorization
- feature space
- variational bayesian
- user preferences
- supervised learning
- least squares
- support vector machine
- feature vectors
- dictionary learning
- unsupervised learning
- tensor factorization
- feature extraction
- personalized ranking
- probabilistic matrix factorization