An explanation-based approach for experiment reproducibility in recommender systems.
Nikolaos PolatidisAntonios PapaleonidasElias PimenidisLazaros IliadisPublished in: Neural Comput. Appl. (2020)
Keyphrases
- recommender systems
- collaborative filtering
- matrix factorization
- user profiles
- user preferences
- information overload
- information filtering
- trust aware
- data sparsity
- recommendation systems
- similarity measure
- recommendation quality
- cold start problem
- user profiling
- implicit feedback
- personalized recommendation
- rating prediction
- user interests
- product recommendation
- user modelling
- user model
- e learning
- collaborative filtering recommender systems