A novel approach based on multi-view reliability measures to alleviate data sparsity in recommender systems.
Sajad AhmadianMohsen AfsharchiMajid MeghdadiPublished in: Multim. Tools Appl. (2019)
Keyphrases
- feature space
- multi view
- data sparsity
- recommender systems
- collaborative filtering
- cold start problem
- matrix factorization
- single view
- multiple views
- three dimensional
- recommendation quality
- depth map
- d objects
- cold start
- user preferences
- range images
- semi supervised
- view synthesis
- multi view clustering
- multi view face detection
- information overload
- recommendation systems
- hybrid recommendation
- multi view images
- recommendation algorithms
- user ratings
- viewpoint
- user profiles
- collaborative filtering algorithms
- multiple viewpoints
- multi view stereo
- surface reconstruction
- user interests
- multi view learning
- free viewpoint
- text mining
- co training