Privacy aware group based recommender system in multimedia services Ahmed M. Elmisery 1 & Seungmin Rho 2 & Mirela Sertovic 3 & Karima Boudaoud 4 & Sanghyun Seo 2 Received: 31 January 2017 /Revised: 16 April 2017 /Accepted: 13 June 2017 # Springer Science+Business Media, LLC 2017 Abstract Recommending similar-interest users’ groups in multimedia services is the problem of detecting for each registered user his/her membership to one interest-group of relevant consumers. The consumers in each interest-group share some relevant preferences which guarantee that the interest-group as a whole satisfies some desired properties of similarity. As a result, forming these interest-groups requires the availability of personal data of different consumers. This is a crucial requirement for different recommender systems. With the increasing trend of service providers to collect a large volume of personal data regarding their end-users, presumably to better serve them. However, a significant part of the data that is typically collected is not essential to the service being offered, or to the completion of the services it was presumably released for. Gathering such unnecessary data can be seen as a privacy threat, and storing it exposes the end-users to further unavoidable risks. In this paper, a Multimed Tools Appl DOI 10.1007/s11042-017-4950-0 * Sanghyun Seo shseo75@gmail.com Ahmed M. Elmisery ahmedmisery@gmail.com Seungmin Rho smrho@sungkyul.ac.kr Mirela Sertovic msertovic@yahoo.com Karima Boudaoud karima@polytech.unice.fr 1 Department of Electronic Engineering, Universidad Tecnica Federico Santa Maria, Valparaiso, Chile 2 Department of Media Software, Sungkyul University, Anyang-si, South Korea 3 Filozofski fakultet u Zagrebu, Sveučilište u Zagrebu, Zagreb, Republika Hrvatska 4 Laboratoire d’Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe RAINBOW, Sophia-Antipolis, France