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 pro-
files often prevent the computation of user similarity. Moreover CF
doesn’t take into account the reliability of the other users. In this
paper1 we present a real world application, namely moleskiing.it, in
which both of these conditions are critic to deliver personalized recom-
mendations. 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 trust-
worthiness. Differently from the notion of authority, we claim that
trustworthiness is a user centered notion that requires the computa-
tion 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.

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