应用人工智能技术来分析旅游目的地的游客
Juan Schrader1, Lloy Pinedo2, Franz Vargas1
1Grupo de Investigación Innovación Turística y Comercio Exterior, Facultad de Ciencias Económicas, Administrativas y Contables, Universidad Nacional Autónoma de Alto Amazonas, Yurimaguas, Peru.
Frontiers in artificial intelligence
|August 20, 2025
概括
机器学习识别了秘鲁阿尔托亚马逊地区的五个不同的旅游资料. 这种细分有助于为当地发展量身定制旅游战略,并增强游客体验.
科学领域:
- 数据科学数据科学数据科学
- 旅游管理 旅游管理
- 机器学习应用 机器学习应用
背景情况:
- 旅游业对秘鲁的当地发展至关重要,但游客的个人资料仍然不明朗.
- 对于像阿尔托亚马逊州这样的目的地,有效的规划和推广需要详细的旅游细分.
研究的目的:
- 用机器学习来描述阿尔托亚马逊地区的游客.
- 为战略规划和推广举措确定不同的访客群体.
主要方法:
- 在数据分析中采用CRISP-DM方法.
- 利用主要组件分析来减少维度.
- 在882个访客调查中应用了聚类算法 (K-Means,DBSCAN,HDBSCAN,Agglomerative).
主要成果:
- 聚合集群模型显示出卓越的内部验证.
- 在阿尔托亚马逊州旅游市场中成功确定了五个不同的游客配置文件.
- 这些部分为产品开发和营销提供了可操作的见解.
结论:
- 机器学习是有效的旅游细分的宝贵工具.
- 经验证据支持使用数据驱动的洞察力来加强新兴目的地.
- 为特定细分市场量身定制服务可以优化游客满意度和目的地竞争力.
关键词:
聚合集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集群集在DBSCAN中,可以使用DBSCAN.在HDBSCAN中使用HDBSCAN.K-意味着K的意思.人工智能的人工智能是人工智能.聚类集群是指聚类的聚类.细分化 细分化的细分化游客是游客,游客是游客.
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