Collaborative Filtering Using Interval Estimation Naïve Bayes

@inproceedings{Robles2003CollaborativeFU,
  title={Collaborative Filtering Using Interval Estimation Na{\"i}ve Bayes},
  author={V{\'i}ctor Robles and Pedro Larra{\~n}aga and Jos{\'e} M. Pe{\~n}a and {\'O}scar Marb{\'a}n and F. Javier Crespo and Mar{\'i}a S. P{\'e}rez-Hern{\'a}ndez},
  booktitle={AWIC},
  year={2003}
}
Personalized recommender systems can be classified into three main categories: content-based, mostly used to make suggestions depending on the text of the web documents, collaborative filtering, that use ratings from many users to suggest a document or an action to a given user and hybrid solutions. In the collaborative filtering task we can find algorithms such as the na ı̈ve Bayes classifier or some of its variants. However, the results of these classifiers can be improved, as we demonstrate… CONTINUE READING