Supervised Convolutional Matrix Factorization for Document Recommendation.
Huiting LiuChao LingLiangquan YangPeng ZhaoPublished in: Int. J. Comput. Intell. Appl. (2018)
Keyphrases
- matrix factorization
- collaborative filtering
- recommender systems
- item recommendation
- data sparsity
- latent factor models
- cold start problem
- low rank
- recommendation systems
- missing data
- personalized ranking
- factorization methods
- nonnegative matrix factorization
- information retrieval systems
- stochastic gradient descent
- rating prediction
- information retrieval
- personalized recommendation
- factor analysis
- document collections
- negative matrix factorization
- implicit feedback
- semi supervised
- user preferences
- document clustering
- tensor factorization
- latent factors
- user profiles
- keywords
- supervised learning
- feature selection
- retrieval systems
- machine learning
- probabilistic model
- probabilistic matrix factorization
- factor matrices
- cold start
- user ratings
- sparse representation
- recommendation algorithms
- relevant documents