Incorporating Auxiliary Information in Collaborative Filtering Data Update with Privacy Preservation
Online shopping has become increasingly popular in recent years. More and more people are willing to buy products through Internet instead of physical stores. For promotional purposes, almost all online merchants provide product recommendations to their returning customers. Some of them ask professional recommendation service providers to help develop and maintain recommender systems while others need to share their data with similar shops for better product recommendations. There are two issues, how to protect customers’ privacy while retaining data utility before they release the data to the third parties; based on how to handle data growth efficiently.
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