Item based recommendation using matrix-factorization-like embeddings from deep networks.
Vaidyanath Areyur ShanthakumarClark BarnettKeith WarnickPutu Ayu SudyantiVitalii GerbuzTathagata MukherjeePublished in: ACM Southeast Conference (2021)
Keyphrases
- matrix factorization
- collaborative filtering
- recommender systems
- data sparsity
- cold start problem
- item recommendation
- low rank
- negative matrix factorization
- cold start
- latent factor models
- recommendation systems
- latent space
- user preferences
- nonnegative matrix factorization
- factorization methods
- recommendation algorithms
- data matrix
- implicit feedback
- personalized recommendation
- factor analysis
- social networks
- stochastic gradient descent
- dimensionality reduction
- probabilistic matrix factorization
- user ratings
- latent factors
- tensor factorization
- variational bayesian
- rating prediction
- user interests
- link prediction
- missing data
- user profiles
- web search