A sub-one quasi-norm-based similarity measure for collaborative filtering in recommender systems.
Shan JiangShu-Cherng FangQi AnJohn E. LaveryPublished in: Inf. Sci. (2019)
Keyphrases
- recommender systems
- collaborative filtering
- similarity measure
- similarity computation
- user based collaborative filtering
- matrix factorization
- user similarity
- data sparsity
- pearson correlation coefficient
- user preferences
- user profiles
- mutual information
- recommendation systems
- information filtering
- pairwise
- cold start
- similarity search
- recommendation algorithms
- recommendation quality
- cold start problem
- content based filtering
- user ratings
- personalized recommendation
- user feedback
- collaborative filtering algorithms
- online dating
- transfer learning
- clustering method
- movie recommendation
- item based collaborative filtering
- objective function
- implicit feedback
- user modeling
- information overload
- user interests
- user model
- similarity function
- euclidean distance
- product recommendation
- netflix prize
- prediction accuracy
- distance measure
- probabilistic matrix factorization
- collaborative filtering recommender systems
- deal with information overload
- user item rating