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- W3201770300 endingPage "104437" @default.
- W3201770300 startingPage "104437" @default.
- W3201770300 abstract "Understanding tourist movements provides insights for destination planning, service design and marketing. The key challenge is to develop a tool that can capture the value in the tourist mobility data. This study presents a new heuristic approach that combines adaptive spatial clustering with frequent pattern mining to improve the performance and efficiency of trajectory data analytics. The aim is to fully leverage the semantic information in the tourist data and the duration that tourists stay at an attraction. Anonymous mobile positioning data from 741 tourists to one of China's leading destinations are used to illustrate the application of the new analytical approach. The results reveal a four-level destination spatial structure ranging from core to peripheral areas. The findings provide practical implications for facilitating intra-destination cooperation and optimizing destination resource allocation and service design." @default.
- W3201770300 created "2021-10-11" @default.
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- W3201770300 date "2022-04-01" @default.
- W3201770300 modified "2023-10-08" @default.
- W3201770300 title "Leveraging tourist trajectory data for effective destination planning and management: A new heuristic approach" @default.
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- W3201770300 doi "https://doi.org/10.1016/j.tourman.2021.104437" @default.
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