Recommender Performance on Collaborative Filtering using Latent Topics under Several Sparsity Levels.
Akihiro NishimuraYoshinori HijikataKosuke SatoPublished in: WI/IAT (2020)
Keyphrases
- collaborative filtering
- latent topics
- data sparsity
- topic modeling
- recommender systems
- topic models
- matrix factorization
- user preferences
- recommendation systems
- latent dirichlet allocation
- user ratings
- making recommendations
- cold start
- latent variables
- personalized recommendation
- user profiles
- probabilistic latent semantic analysis
- probabilistic topic models
- artificial intelligence
- bag of words
- co occurrence
- text mining
- image processing
- databases
- text documents
- recommendation algorithms
- nearest neighbor
- high dimensional
- natural language
- pattern recognition