[Objective] This paper explores the characteristics of a city portrait’s evolution based on visitor’s cognitive data with time attributes. [Methods] First, we chose the urban tourism industry as our research subject. Then, we developed a method using the LDA model and multi-dimensional theme description framework for the city. Finally, we revealed the changing trends of the city portraits from three perspectives: the theme development process, as well as the theme evolution trends in the first and second feature dimensions. [Results] We examined our new model with Hong Kong and found its urban tourism portraits showed no significant periodic changes. However, the tourists’ perceptions on Hong Kong always had the primary and secondary dimensions. Sightseeing, transportation and entertainment were the main factors of tourists’ perceptions on Hong Kong. Specifically, sightseeing was the most important one during the entire process, entertainment was mainly in the early and late stages, and transportation was more likely at the middle stage. We also found each topic node in the evolutionary path had a stable iconic. [Limitations] We need to evaluate our method with other cities. [Conclusions] Our research will benefit urban planning and policy implementation.
叶光辉,徐彤,毕崇武,李心悦. 基于多维度特征与LDA模型的城市旅游画像演化分析*[J]. 数据分析与知识发现, 2020, 4(11): 121-130.
Ye Guanghui,Xu Tong,Bi Chongwu,Li Xinyue. Analyzing Evolution of City Tourism Portraits with Multi-Dimensional Features and LDA Model. Data Analysis and Knowledge Discovery, 2020, 4(11): 121-130.
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