Personalized preference elicitation in recommender systems using matrix factorization.
Kirk IsermanYuhong LiuPublished in: ACSSC (2017)
Keyphrases
- matrix factorization
- preference elicitation
- recommender systems
- personalized recommendation
- collaborative filtering
- user profiles
- user model
- utility function
- low rank
- multi criteria
- user preferences
- decision theory
- cold start problem
- implicit feedback
- nonnegative matrix factorization
- data sparsity
- factor analysis
- factorization methods
- negative matrix factorization
- probabilistic matrix factorization
- recommendation systems
- user interests
- user feedback
- tensor factorization
- combinatorial auctions
- privacy issues
- cold start
- multiple agents
- preference relations
- latent factors
- data sets
- decision making
- multi agent
- social media
- decision makers
- user ratings
- recommendation algorithms
- multi attribute