Machine Learning Applications in Smart Tourism: Overview, Research Challenges, and the Road Ahead | EAI Endorsed Transactions on Tourism, Technology and Intelligence

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However, as an industry facing increasing competition on a global scale, tourism needs to embrace technologies to adapt quickly to changes. The emergence of smart tourism offers a route to achieve a competitive edge. To this end, machine learning techniques are used to analyze the abundant data available, forecast trends and and provide best solutions. This paper provides an overview, challenges and future directions of research on machine learning techniques applied in smart tourism. 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Duong"/> <meta name="DC.Date.created" scheme="ISO8601" content="2024-08-01"/> <meta name="DC.Date.dateSubmitted" scheme="ISO8601" content="2024-06-14"/> <meta name="DC.Date.issued" scheme="ISO8601" content="2024-09-24"/> <meta name="DC.Date.modified" scheme="ISO8601" content="2024-11-15"/> <meta name="DC.Description" xml:lang="en" content="Tourism plays a vital role in stimulating economic growth, creating employment opportunities and facilitating cultural exchange and mutual understanding between people of different backgrounds. However, as an industry facing increasing competition on a global scale, tourism needs to embrace technologies to adapt quickly to changes. The emergence of smart tourism offers a route to achieve a competitive edge. To this end, machine learning techniques are used to analyze the abundant data available, forecast trends and and provide best solutions. 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However, as an industry facing increasing competition on a global scale, tourism needs to embrace technologies to adapt quickly to changes. The emergence of smart tourism offers a route to achieve a competitive edge. To this end, machine learning techniques are used to analyze the abundant data available, forecast trends and and provide best solutions. This paper provides an overview, challenges and future directions of research on machine learning techniques applied in smart tourism.</p> </section> <section class="item references"> <h2 class="label"> References </h2> <div class="value"> <p>[1] Hui Ma. “Development of a smart tourism service system based on the Internet of Things and machine learning”. In: Journal of Supercomputing 80 (5 Mar. 2024), pp. 6725–6745. issn: 15730484. doi: 10 . 1007 / s11227-023-05719-w. </p> <p>[2] Ton Jaitrong and Aziz Nanthaamornphong. “Classification of Tourism-Related Topics in Phuket: A Case Study”. 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Machine Learning Applications in Smart Tourism: Overview, Research Challenges, and the Road Ahead | EAI Endorsed Transactions on Tourism, Technology and Intelligence