An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Collaborative filtering with privacy via factor analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Collaborative Filtering Using Principal Component Analysis and Fuzzy Clustering
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Collaborative Filtering with Privacy
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
Privacy practices of Internet users: self-reports versus observed behavior
International Journal of Human-Computer Studies - Special isssue: HCI research in privacy and security is critical now
A Collaborative Filtering Algorithm Employing Genetic Clustering to Ameliorate the Scalability Issue
ICEBE '06 Proceedings of the IEEE International Conference on e-Business Engineering
Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
Enhancing privacy and preserving accuracy of a distributed collaborative filtering
Proceedings of the 2007 ACM conference on Recommender systems
An Architecture for Privacy Preserving Collaborative Filtering on Web Portals
IAS '07 Proceedings of the Third International Symposium on Information Assurance and Security
Collaborative recommender systems: Combining effectiveness and efficiency
Expert Systems with Applications: An International Journal
Applications of wavelet data reduction in a recommender system
Expert Systems with Applications: An International Journal
Using error-correcting dependencies for collaborative filtering
Data & Knowledge Engineering
Robust fuzzy clustering-based image segmentation
Applied Soft Computing
A Collaborative Filtering Algorithm Based on Rough Set and Fuzzy Clustering
FSKD '08 Proceedings of the 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
An iterative semi-explicit rating method for building collaborative recommender systems
Expert Systems with Applications: An International Journal
A collaborative filtering method based on artificial immune network
Expert Systems with Applications: An International Journal
Collaborative filtering using orthogonal nonnegative matrix tri-factorization
Information Processing and Management: an International Journal
WISM '09 Proceedings of the 2009 International Conference on Web Information Systems and Mining
Collaborative filtering with ordinal scale-based implicit ratings for mobile music recommendations
Information Sciences: an International Journal
Improving the scalability of recommender systems by clustering using genetic algorithms
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
Improving Privacy-Preserving NBC-Based Recommendations by Preprocessing
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
A novel self-organizing map (SOM) neural network for discrete groups of data clustering
Applied Soft Computing
An improved privacy-preserving DWT-based collaborative filtering scheme
Expert Systems with Applications: An International Journal
An Improved Profile-Based CF Scheme with Privacy
ICSC '11 Proceedings of the 2011 IEEE Fifth International Conference on Semantic Computing
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A scalable privacy-preserving recommendation scheme via bisecting k-means clustering
Information Processing and Management: an International Journal
An entropy-based neighbor selection approach for collaborative filtering
Knowledge-Based Systems
Robustness analysis of privacy-preserving model-based recommendation schemes
Expert Systems with Applications: An International Journal
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Privacy-preserving collaborative filtering (PPCF) methods designate extremely beneficial filtering skills without deeply jeopardizing privacy. However, they mostly suffer from scalability, sparsity, and accuracy problems. First, applying privacy measures introduces additional costs making scalability worse. Second, due to randomness for preserving privacy, quality of predictions diminishes. Third, with increasing number of products, sparsity becomes an issue for both CF and PPCF schemes. In this study, we first propose a content-based profiling (CBP) of users to overcome sparsity issues while performing clustering because the very sparse nature of rating profiles sometimes do not allow strong discrimination. To cope with scalability and accuracy problems of PPCF schemes, we then show how to apply k-means clustering (KMC), fuzzy c-means method (FCM), and self-organizing map (SOM) clustering to CF schemes while preserving users' confidentiality. After presenting an evaluation of clustering-based methods in terms of privacy and supplementary costs, we carry out real data-based experiments to compare the clustering algorithms within and against traditional CF and PPCF approaches in terms of accuracy. Our empirical outcomes demonstrate that FCM achieves the best low cost performance compared to other methods due to its approximation-based model. The results also show that our privacy-preserving methods are able to offer precise predictions.