Moleskiing.it: a Trust-aware Recommender System for Ski Mountaineering

Recommender Systems (RS) suggest to users items they will like based on their past opinions. Collaborative Filtering (CF) is the most used technique and works by recommending to the active user items appreciated by similar users. However the sparseness of user proles often prevent the computation of user similarity. Moreover CF doesn’t take into account the reliability of the other users. In this paper 1 we present a real world application, namely moleskiing.it, in which both of these conditions are critic to deliver personalized recommendations. A blog oriented architecture collects user experiences on ski mountaineering and their opinions on other users. Exploitation of Trust Metrics allows to present only relevant and reliable information according to the user’s personal point of view of other authors trustworthiness. Dieren tly from the notion of authority, we claim that trustworthiness is a user centered notion that requires the computation of personalized metrics. We also present an open information exchange architecture that makes use of Semantic Web formats to guarantee interoperability between ski mountaineering communities. 1 This work is based on an earlier work: \A Trust-enhanced Recommender System