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A Recommendation System for Enhancing the Personalized Search Itineraries in the Public Transportation Domain

In traditional transport information systems, the users must explicitly provide the information related to both their profiles and travels to receive a personalized response. However, this requires, among others, an extra effort from user in term of search time. We aim to identify not only implicitly users’ information, but also to anticipate their need even if some data are missing through a recommender system based on collaborative filtering technique. In this work, the information related to users is represented using the ontology which proved far more adequate model for representing semantically data.