Abstract
Recommending pertinent Place Of Interests (POIs) is a desirable feature for mobile users, and which is generally served by for-profit proprietary platforms, such as Yelp, TripAdvisor, etc. However, the siloed design of these platforms raises today several issues about privacy, user data portability, and algorithm transparency. To address these issues, we propose a decoupled recommender system (RS) architecture. The idea consists of externalizing the sensitive features, such as the users’ preferences and the underlying RS algorithm, from the service’s application. Hence, the proposed RS operates as an interchangeable third-party service. We conducted several experiments to evaluate the impact of the decentralization, and we were able to improve the performances by relying on Linked Open Data (LOD) and on an appropriate similarity measure.
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Boubenia, M., Bouyakoub, F.M., Belkhir, A. (2021). A User-Side POIs Mobile Recommender System. In: Senouci, M.R., Boudaren, M.E.Y., Sebbak, F., Mataoui, M. (eds) Advances in Computing Systems and Applications. CSA 2020. Lecture Notes in Networks and Systems, vol 199. Springer, Cham. https://doi.org/10.1007/978-3-030-69418-0_18
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