Trust-based recommendations for mobile tourists in TIP

Abstract

Recommender systems aim to suggest to users items they would like. However, concerns about the reliability of information from unknown recommenders influences user acceptance. In this paper, we analyse trust-based recommendations for the tourist information system TIP. We believe that the recommender strategy is closely related to the information domain applied. So, the delivered trust-based tourist recommendations have combined peers’ ratings on sights, trust computations and geographical constraints. We create two trust propagation models to spread trust in the TIP community. Three Trust based and location-aware filtering algorithms are implemented. According to research on feasibilities of trust in recommendation fields, three collaborative filtering algorithms in TIP are improved by introducing the trust concept.