A scalable privacy-preserving recommendation scheme via bisecting k-means clustering
A novel bisecting k-means clustering-based privacy-preserving CF scheme is proposed. A two-level preprocessing scheme is suggested to enhance scalability and accuracy. Effects of scalability and sparseness challenges are alleviated considerably. Accuracy of the solution is significantly better than knn-based CF and PPCF methods.
accuracy binary decision diagrams clustering methods data preprocessing data privacy recommender systems