Abstract
Travel route planning is an important part of traveler’s tourism planning to make the travel more healthier and to improve the tourists’ satisfying and wellbeing.With the continuous accumulation of network resources, tourists are faced with the problem of information overload when they are planning the travel route. In this work, a new method of travel path mining is proposed, which takes the topic hierarchy of scenic spots and the features of scenic spots into consideration. First of all, the travel text data is captured by the network crawler software, and after the preprocessing of the data, such as word segmenting and denoising, the standardized travel data set is formed. Then, according to the location information of hot scenic spots in the travel notes, carry out the topic stratification of the scenic spots and construct the travel path data set. Finally, the travel route is excavated by taking into account the topic hierarchy and the features of a scenic spot. The experimental results show that the proposed method can effectively extract the travel route from the mass texts of travel notes.
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Acknowledgements
The authors acknowledge the Sichuan Federation of Social Science Associations (No. SC16XK033), The Ministry of Culture and Tourism (No. WMYC20181-025), The Education Department of Sichuan Province (No. 18ZA0366). The cooperation and innovation center of the competitiveness of Sichuan and Tibet tourism industry (No. 17CZZX01), Sichuan Tourism University (No. SCTUJ1709; No. SCTUJ1809), Sichuan Tourism Research Center (No. LYC17-35), Chengdu Science and Technology Bureau (No. 017-RK00-00462-ZF).
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Du, S., Zhang, H., Xu, H. et al. To make the travel healthier: a new tourism personalized route recommendation algorithm. J Ambient Intell Human Comput 10, 3551–3562 (2019). https://doi.org/10.1007/s12652-018-1081-z
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DOI: https://doi.org/10.1007/s12652-018-1081-z