Accelerating model-based collaborative filtering with item clustering.
Robin DevooghtHugues BersiniPublished in: IJCNN (2018)
Keyphrases
- collaborative filtering
- clustering algorithm
- collaborative filtering recommendation algorithm
- user ratings
- user preferences
- cold start problem
- making recommendations
- k means
- pearson correlation coefficient
- item recommendation
- recommender systems
- personalized recommendation
- matrix factorization
- cold start
- clustering method
- cluster analysis
- recommendation algorithms
- anomaly detection
- data sparsity
- recommendation systems
- latent factor models
- data clustering
- graph theoretic
- data objects
- interval estimation
- active user
- unsupervised learning
- categorical data
- content based filtering
- user specific
- data sets
- distance metric
- prediction accuracy
- high dimensional data
- probabilistic model
- knowledge base