基于人工智能深度挖掘的5A级旅游景区空间意象研究
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Research on the Spatial Image of 5A-level Tourist Attractions Based on Deep Mining of Artificial Intelligence
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    摘要:

    数字时代背景下人工智能技术的发展拓宽了数据的获取渠道。以5A级旅游景区为研究对象,利用官方平台的名录及属性数据和ChatGPT深度合成的文本数据挖掘隐性知识,采用描述性及推断性数理统计方法识别旅游景区关键空间意象要素,分析先天条件及后天干预与空间意象之间的关系。结果表明:(1)标志物是游客印象中区别不同景区的主要依据,也是个体景区获得较高游客意象评价的关键;(2)标志物、区域和道路构成5A级景区整体空间意象的基础和主体;(3)后天设计对意象的影响至关重要,标志物打造和区域划分是后天设计环节中的重点。旨在可促进景区规划设计提升及高质量发展,推动精细化形象宣传和管理。

    Abstract:

    In the context of the digital age, the development of artificial intelligence technology has broadened the access to data. In this study, we took 5A-level tourist attractions as the research object, used the directory and attribute data of the official platform and the text data deeply synthesized by ChatGPT to mine tacit knowledge, used descriptive and inferential mathematical statistics methods to identify the key spatial image elements of tourist attractions, and analyzed the relationship between congenital conditions and acquired intervention and spatial imagery. The results show that: (1) Markers are the primary basis for distinguishing different scenic spots in tourists’ impressions, and they are also the key to obtaining higher tourist image evaluation for individual scenic spots. (2) Landmarks, areas, and roads constitute the basis and main body of the overall spatial image of 5A-level scenic spots. (3) The influence of acquired design on imagery is significant, and the creation of markers and regional divisions are the key points in the acquired design process. This study can improve scenic spot planning, design, and high-quality development and promote refined image publicity and management.

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  • 在线发布日期: 2025-01-20
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