Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations.
Filippo BetelloFederico SicilianoPushkar MishraFabrizio SilvestriPublished in: ECIR (2) (2024)
Keyphrases
- recommender systems
- training data
- manually labeled training data
- collaborative filtering
- matrix factorization
- training set
- supervised learning
- test data
- user profiling
- class labels
- cold start problem
- decision trees
- data sets
- information filtering
- training process
- learned from training data
- test set
- user preferences
- training samples
- trust aware
- labeled data
- prior knowledge
- classification accuracy
- information retrieval
- recommendation quality
- labelled data
- personal preferences
- user modelling
- personalized recommendation
- user modeling
- generalization error
- user feedback
- semi supervised learning
- hidden markov models