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传统的统计手段可以获得旅游城市或景点的游客量,而无法获得旅游客源地游客量,本文首先把互联网搜索数据与现实游客行为之间进行关联和映射,然后将搜索量最高关键词通过自由组合和非线性多项式拟合,发现3个词组合时与现实游客行为之间R2高达0.999,最后反演出2011—2014年中国(港澳台除外)各省、直辖市和自治区至甘肃省旅游的人数,进行甘肃省旅游客源地时空数据可视化、时空数据异常探测、时空过程分析等,帮助旅游部门了解游客的来源及去处、游客的出行规律和爱好偏向,做出有针对性的决策。
The traditional statistical methods can get the tourists in tourist cities or scenic spots, but can not get tourists from tourist sources. This paper first correlates and maps the Internet search data with the real tourists’ behaviors, and then passes the keywords with the highest search quantity through the free Combination and non-linear polynomial fitting, it is found that the R2 between the three-word combination and the real tourist behavior is as high as 0.999, and finally the number of tourists traveling from provinces, municipalities and autonomous regions to Gansu Province from 2011 to 2014 in China (excluding Hong Kong, Maucao, Taiwan) Gansu Province tourist source spatial and temporal data visualization, spatial and temporal data anomaly detection, analysis of space-time process, to help tourism departments understand the source and destination of tourists, tourists travel patterns and preferences, to make targeted decisions.