A Mechanism to Improve Effectiveness and Privacy Preservation for Review Publication in LBS

Local business service systems (LBSS), as an essential role of location-based service (LBS), have been gaining tremendous popularity in our daily life. Individuals' reviews in these systems are very important as they not only contribute to building reputations for businesses but also play a guiding role for consumers. However, users' privacy disclosure and the effectiveness of reviews are the urgent problems to be solved for the further development of LBSS. This paper proposes a mechanism to improve effectiveness and privacy preservation for review publication. In users' privacy protection, the mechanism firstly formalizes the model of attackers, then focuses on the identification or inference attack caused by reviews. For improving the effectiveness of reviews, the mechanism introduces users' reputation scores to rank the reviews. We evaluate our mechanism thoroughly by extensive experiments, and the results validate that our mechanism can achieve a better performance.