Information Security Commons^™

Data Privacy Preservation In Collaborative Filtering Based Recommender Systems, Xiwei Wang

Theses and Dissertations--Computer Science

This dissertation studies data privacy preservation in collaborative filtering based recommender systems and proposes several collaborative filtering models that aim at preserving user privacy from different perspectives.

The empirical study on multiple classical recommendation algorithms presents the basic idea of the models and explores their performance on real world datasets. The algorithms that are investigated in this study include a popularity based model, an item similarity based model, a singular value decomposition based model, and a bipartite graph model. Top-N recommendations are evaluated to examine the prediction accuracy.

It is apparent that with more customers' preference data, recommender systems …