Using Collaborative Filtering to Overcome the Curse of Dimensionality when Clustering Users in a Group Recommender System.
Ludovico BorattoSalvatore CartaPublished in: ICEIS (2) (2014)
Keyphrases
- recommender systems
- collaborative filtering
- online dating
- matrix factorization
- recommendation quality
- cold start problem
- data sparsity
- recommendation systems
- product recommendation
- cold start
- implicit feedback
- user preferences
- user profiles
- information overload
- user interests
- active user
- user ratings
- k means
- collaborative filtering algorithms
- information filtering
- content based filtering
- personalized recommendation
- clustering method
- deal with information overload
- user model
- trust aware
- user feedback
- clustering algorithm
- making recommendations
- homogeneous groups
- netflix prize
- user item rating
- user similarity
- personalized services
- user specific
- recommendation algorithms
- user modeling
- unsupervised learning
- rating prediction
- similar objects
- social media