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Toward Geospatial Collaborative Tourism Recommender Systems
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Author(s): Zahra Bahramian (University of Tehran, Iran), Rahim Ali Abbaspour (University of Tehran, Iran)and Christophe Claramunt (Naval Academy Research Institute, France)
Copyright: 2018
Pages: 37
Source title:
GIS Applications in the Tourism and Hospitality Industry
Source Author(s)/Editor(s): Somnath Chaudhuri (Maldives National University, Maldives)and Nilanjan Ray (Adamas University, India)
DOI: 10.4018/978-1-5225-5088-4.ch010
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Abstract
Tourism activities are highly dependent on spatial information. Finding the most interesting travel destinations and attractions and planning a trip are still open research issues to GIScience research applied to the tourism domain. Nowadays, huge amounts of information are available over the world wide web that may be useful in planning a visit to destinations and attractions. However, it is often time consuming for a user to select the most interesting destinations and attractions and plan a trip according to his own preferences. Tourism recommender systems (TRSs) can be used to overcome this information overload problem and to propose items taking into account the user preferences. This chapter reviews related topics in tourism recommender systems including different tourism recommendation approaches and user profile representation methods applied in the tourism domain. The authors illustrate the potential of tourism recommender systems as applied to the tourism domain by the implementation of an illustrative geospatial collaborative recommender system using the Foursquare dataset.
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