A personalized mobile travel recommender system using hybrid algorithm

The modern era witnesses the evolution of handheld devices from a simple communication medium to a sophisticated information access platform. Coupling it with intelligent recommendation techniques can transform it to an essential companion for users during their travel, purchases and other routine transactions. A recommender system extracts personalized information relevant to users, thereby limiting the information overload. Our application, Buddy@Move is a hybrid travel recommender which brings together the features of content-based, collaborative and demographic filtering techniques. While travel imprints of the user cater to content-based filtering, resulting in personalized recommendations, the societal transactions provide input for the collaborative portion. The system will make use of the individual demographic information, to suggest what suits the user thereby making it more intelligent and user acceptable.