A Hybrid Strategy for Privacy-Preserving Recommendations for Mobile Shopping

Provided by: RWSoftware
Topic: Mobility
Format: PDF
To calculate recommendations, recommender systems collect and store huge amounts of users' personal data such as preferences, interaction behavior, or demographic information. If these data are used for other purposes or get into the wrong hands, the privacy of the users can be compromised. Thus, service providers are confronted with the challenge of offering accurate recommendations without the risk of dissemination of sensitive information. This paper presents a hybrid strategy combining collaborative filtering and content-based techniques for mobile shopping with the primary aim of preserving the customer's privacy.

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