Estimating NBC-based recommendations on arbitrarily partitioned data with privacy

Providing partitioned data-based recommendations has been receiving increasing attention due to mutual advantages. In case of limited data, it is not likely to estimate accurate and reliable predictions. Therefore. e-commerce sites holding insufficient ratings prefer offering predictions to their customers based on integrated data. However, users' preferences about products are considered online vendors' confidential and valuable assets; and they do not want to disclose them their partners during collaborative prediction processes.