A method for privacy-preserving context-aware mobile recommendations

Polatidis, Nikolaos; Georgiadis, Christos; Pimenidis, Elias; Stiakakis, Emmanouil

Abstract

Mobile recommender systems aim to solve the information overload problem found by recommending products or services to users of mobile smartphones or tables at any given point in time and in any possible location. Mobile recommender systems are designed for the specific goal of mobile rec-ommendations, such as mobile commerce or tourism and are ported to a mobile device for this purpose. They utilize a specific recommendation method, like collaborative filtering or content-based filtering and use a considerable amount of contextual information in order to provide more personalized recommendations. However due to privacy concerns users are not willing to provide the required personal information to make these systems usable. In response to the privacy concerns of users we present a method of privacy preserving context-aware mobile recommendations and show that it is both practical and effective.

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: 6th International Conference on e-Democracy
• Start Date: Dec 10, 2015
• End Date: Dec 11, 2015
• Publication Date: Jul 28, 2015
• Peer Reviewed: Peer Reviewed
• Pages: 62-74
• Keywords: mobile recommender systems, context-awareness, privacy, privacy-preserving systems
• Public URL: https://uwe-repository.worktribe.com/output/830927
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-27164-4_5
• Additional Information: Title of Conference or Conference Proceedings : E-Democracy – Citizen Rights in the World of the New Computing Paradigms: Volume 570 of the series Communications in Computer and Information Science