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Deepanjal Shrestha, Tan Wenan, Deepmala Shrestha, Neesha Rajkarnikar and Seung-Ryul Jeong
This study introduces a data-driven and machine-learning approach to design a personalized tourist recommendation system for Nepal. It examines key tourist attributes, such as demographics, behaviors, preferences, and satisfaction, to develop four sub-mo...
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Leyla Gamidullaeva, Alexey Finogeev, Mikhail Kataev and Larisa Bulysheva
Despite of tourism infrastructure and software, the development of tourism is hampered due to the lack of information support, which encapsulates various aspects of travel implementation. This paper highlights a demand for integrating various approaches ...
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Luz Santamaria-Granados, Juan Francisco Mendoza-Moreno and Gustavo Ramirez-Gonzalez
Recommendation systems have overcome the overload of irrelevant information by considering users? preferences and emotional states in the fields of tourism, health, e-commerce, and entertainment. This article reviews the principal recommendation approach...
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Markos Konstantakis, Georgios Alexandridis and George Caridakis
Recent developments in digital technologies regarding the cultural heritage domain have driven technological trends in comfortable and convenient traveling, by offering interactive and personalized user experiences. The emergence of big data analytics, r...
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