Impact of Content Novelty on the Accuracy of a Group Recommender System.
Ludovico BorattoSalvatore CartaPublished in: DaWaK (2014)
Keyphrases
- recommender systems
- high accuracy
- collaborative filtering
- prediction accuracy
- neural network
- user interests
- multimedia content
- computational cost
- classification accuracy
- precision and recall
- multimedia data
- error rate
- novelty detection
- group members
- user generated content
- user experience
- computational efficiency
- semantic information
- database
- active learning
- computational complexity
- metadata
- information retrieval
- data sets