Exploiting the User Social Context to Address Neighborhood Bias in Collaborative Filtering Music Recommender Systems.
Diego Sánchez-MorenoVivian F. López BatistaMaría Dolores Muñoz VicenteÁngel Luis Sánchez LázaroMaría N. Moreno GarcíaPublished in: Inf. (2020)
Keyphrases
- recommender systems
- collaborative filtering
- social context
- user preferences
- recommendation quality
- music recommendation
- matrix factorization
- user profiles
- user ratings
- cold start problem
- cold start
- information overload
- recommendation systems
- user interests
- data sparsity
- user model
- item recommendation
- product recommendation
- recommendation algorithms
- personalized recommendation
- collaborative filtering recommender systems
- social interaction
- active user
- implicit feedback
- virtual world
- user profiling
- content based filtering
- information filtering
- user modeling
- collaborative filtering algorithms
- social relations
- item based collaborative filtering
- probabilistic matrix factorization
- user feedback
- contextual information
- social relationships
- online dating
- netflix prize
- hybrid recommendation
- music information retrieval
- domain independent
- user generated content