based on microaggregation, which provides accurate recommendations estimated from
perturbed data whilst guaranteeing user k-anonymity. The experimental results presented in
this article show the effectiveness of the proposed technique in protecting users' privacy
without compromising the quality of the recommendations. In this sense, the proposed
approach perturbs data in a much more efficient way than other well-known methods such …