Improving collaborative filtering's rating prediction accuracy by introducing the experiencing period criterion.
Dionisis MargarisDimitris SpiliotopoulosCostas VassilakisDionysios VasilopoulosPublished in: Neural Comput. Appl. (2023)
Keyphrases
- prediction accuracy
- collaborative filtering
- user ratings
- recommender systems
- ensemble methods
- matrix factorization
- improve the prediction accuracy
- predictive accuracy
- rating prediction
- predictive power
- collaborative filtering algorithms
- data sparsity
- user preferences
- pearson correlation coefficient
- improved accuracy
- graphical models
- web page prediction
- recommendation quality
- collaborative filtering recommendation algorithm
- information retrieval
- demographic information
- text classification
- association rules
- support vector
- feature selection