Company recommendation for new graduates via implicit feedback multiple matrix factorization with Bayesian optimization.
Masahiro KazamaIssei SatoHaruaki YatabeTairiku OgiharaTetsuro OnishiHiroshi NakagawaPublished in: IEEE BigData (2016)
Keyphrases
- matrix factorization
- implicit feedback
- collaborative filtering
- recommender systems
- item recommendation
- personalized ranking
- low rank
- cold start
- explicit feedback
- data sparsity
- cold start problem
- missing data
- negative matrix factorization
- tensor factorization
- latent factors
- eye tracking
- nonnegative matrix factorization
- factor analysis
- user behavior
- latent factor models
- factorization methods
- personalized recommendation
- learning algorithm
- bayesian analysis
- recommendation systems
- user feedback