• DOI:10.1007/978-3-319-90092-6_10
Corpus ID: 19127262

Rating-Based Collaborative Filtering: Algorithms and Evaluation

@inproceedings{Kluver2018RatingBasedCF,
  title={Rating-Based Collaborative Filtering: Algorithms and Evaluation},
  author={Daniel Kluver and Michael D. Ekstrand and J. Konstan},
  booktitle={Social Information Access},
  year={2018}
}

• Daniel Kluver, Michael D. Ekstrand, J. Konstan
• Published in Social Information Access 2018
• Computer Science

Recommender systems help users find information by recommending content that a user might not know about, but will hopefully like. Rating-based collaborative filtering recommender systems do this by finding patterns that are consistent across the ratings of other users. These patterns can be used on their own, or in conjunction with other forms of social information access to identify and recommend content that a user might like. This chapter reviews the concepts, algorithms, and means of… Expand

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