旅游
协同过滤
计算机科学
旅游胜地
推荐系统
万维网
吸引力
情报检索
地理
考古
语言学
哲学
作者
Yufeng Jiang,Yushu Zhang,Zhu-Jun Li,Wendong Yu,Hongwei Wei,Yandan Lin
出处
期刊:Communications in computer and information science
日期:2024-01-01
卷期号:: 226-235
标识
DOI:10.1007/978-981-97-0827-7_20
摘要
Recently, with the development of social and economic levels and people's pursuit of quality of life, tourism has become the first choice for more and more people. However, the traditional travel agency-based tourism method has also begun to expose some problems. However, with the development of machine learning and big data technology, personalized recommendation systems have become more and more important, which also provides us with new ideas to solve this problem. This paper therefore explores the application of spatial clustering algorithm and collaborative filtering algorithm in tourist attraction recommendation. This algorithm can not only mine the geographical location information of tourist attractions, but also analyze and study the data connections between users and attractions, and use these data to make personalized recommendations, providing more considerate and convenient services for travel planning.
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