Privacy-Preserving Collaborative Recommendation Systems Based on the Scalar Product
نویسندگان
چکیده
In the e-commerce era, recommendation systems were introduced to share customer experience and comments. At the same time, there is a need for Ecommerce entities to join their recommender system databases to enhance the reliability toward prospective customers and also to maximize the precision of target marketing. However, there will be a privacy disclosure hazard while joining recommender system databases. In order to preserve privacy in merging recommender system databases, we design a novel algorithm based on ElGamal scheme of homomorphic encryption.
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