Leveraging User Embeddings and Text to Improve CTR Predictions With Deep Recommender Systems.
Carlos Miguel PatiñoCamilo VelásquezJuan Manuel MuñozJuan Manuel GutiérrezDavid Ricardo ValenciaCristian Bartolome AramburuPublished in: RecSys Challenge (2020)
Keyphrases
- recommender systems
- collaborative filtering
- user model
- user preferences
- user profiles
- user ratings
- collaborative filtering recommender systems
- information overload
- user modeling
- information retrieval
- user interests
- user profiling
- user experience
- online advertising
- user feedback
- recommendation systems
- user modelling
- cold start problem
- active user
- personal preferences
- recommendation quality
- recommendation algorithms
- matrix factorization
- user interaction
- end users
- user interface
- manifold learning
- text retrieval
- user queries
- high dimensional data
- data sparsity
- document collections
- content based filtering
- text classification
- relevance feedback