Corpus ID: 571110

RUST M ETRICS IN R ECOMMENDER SYSTEMS : A SURVEY

@inproceedings{Moghaddam2015RUSTME,
  title={RUST M ETRICS IN R ECOMMENDER SYSTEMS : A SURVEY},
  author={M. Moghaddam and N. Mustapha and A. Mustapha and N. Sharef and Anousheh Elahian},
  year={2015}
}
  • M. Moghaddam, N. Mustapha, +2 authors Anousheh Elahian
  • Published 2015
  • Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing of information that lead following the information flow in real world be impossible. Recommender systems, as the most successful application of information filtering, help users to find items of their interest from huge datasets. Collaborative filtering, as the most successful technique for recommendation, utilises social behaviours of users to detect their interests. Traditional challenges of… CONTINUE READING

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