A Social Formalism and Survey for Recommender Systems

@article{Bernardes2014ASF,
  title={A Social Formalism and Survey for Recommender Systems},
  author={Daniel Bernardes and Mamadou Diaby and Rapha{\"e}l Fournier-S'niehotta and Françoise Fogelman-Souli{\'e} and Emmanuel Viennet},
  journal={SIGKDD Explorations},
  year={2014},
  volume={16},
  pages={20-37}
}
This paper presents a general formalism for Recommender Systems based on Social Network Analysis. After introducing the classical categories of recommender systems, we present our Social Filtering formalism and show that it extends association rules, classical Collaborative Filtering and Social Recommendation, while providing additional possibilities. This allows us to survey the literature and illustrate the versatility of our approach on various publicly available datasets, comparing our… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 16 references

Link Prediction in Complex Networks: A Survey

ArXiv • 2010
View 4 Excerpts
Highly Influenced

Evaluating Recommendation Systems

Recommender Systems Handbook • 2011
View 4 Excerpts
Highly Influenced

Recommender systems survey

View 5 Excerpts
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