2019
DOI: 10.1007/s11227-019-03010-5
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Clustering of tourist routes for individual tourists using sequential pattern mining

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Cited by 11 publications
(5 citation statements)
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“…Some other studies help enterprises manage by clustering tourists. Lee and Han grouped tourists with similar travel itineraries and provided them with services such as tour buses, drivers, and guides, saving tourists' costs [23]. Derek et al clustered tourists by their activities at the destination, the framework can describe the demographic characteristics of each group and travel patterns, providing specific destination management [24].…”
Section: A User Clusteringmentioning
confidence: 99%
See 1 more Smart Citation
“…Some other studies help enterprises manage by clustering tourists. Lee and Han grouped tourists with similar travel itineraries and provided them with services such as tour buses, drivers, and guides, saving tourists' costs [23]. Derek et al clustered tourists by their activities at the destination, the framework can describe the demographic characteristics of each group and travel patterns, providing specific destination management [24].…”
Section: A User Clusteringmentioning
confidence: 99%
“…Equation (15) indicates that the objective function combines three aspects of location hotness, favorability, and the degree of satisfying visitor demand; equation (16) and equation ( 17) specify the start and end points of the route; equation (18) indicates that each location can be selected at most once; equation (19) specifies the connectivity of attractions and restaurants within the same day; equation (20) indicates that the previous day must end with a hotel and the next day begins with a hotel, specifying hotel connectivity; equation (21) indicates that there can be no returning streams; equation (22) indicates that there can be no subloops; equation (23) specifies that one must travel from one point to another; equation (24) and equation ( 25) are used to calculate the arrival time for location j; equation (26) and equation ( 27) are used to calculate the departure time of location j; equation (28) specifies that the departure time from the starting point and the hotel is ''0''; equation (29) and equation (30) are the time window constraints; equation (31) constrains that the daily travel time must not exceed a certain value.…”
Section: ) Modeling Of Travel Itinerary Customizationmentioning
confidence: 99%
“…By leveraging the internal pushing force, researchers can systematically elaborate the causes of tourism behavior, and the objective of the tourism experience the tourists desire to obtain. From the academic perspective of the external pulling force, it is represented as the attraction of landscape attributes; such attributes are generally embodied by the cultural ambiance, accommodation, and transportation (Lee and Han, 2020). Based on these analyses, academia has proposed the attribution model of loyalty to the tourism destination, and it is recognized that the tourists' perception of the external pulling force, which is derived from the destination, is generally embodied by the factors such as safety, expression of hospitality, and features of scenic areas (Suhartanto et al, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…erefore, to narrow this gap between supply and demand and reduce the negative impact on tourism, the tourism industry must build an information service platform based on the Internet, and provide targeted services for tourists through data collection and analysis. e widespread use of mobile Internet, especially mobile Internet, has laid the groundwork for meeting the real-time information needs of tourists; however, the explosive growth of information has caused an information overload, which has caused problems for tourists in choosing from the vast amount of tourism information [4]. On the other hand, the characteristics of tourism activity itself make travelers encounter various temporary or unexpected problems in the process, so tourism service providers should focus their service quality improvement on solving these problems and devote themselves to proposing various personalized solutions.…”
Section: Introductionmentioning
confidence: 99%