首页|基于协同过滤算法的旅游景点可视化分析系统的设计与实现

基于协同过滤算法的旅游景点可视化分析系统的设计与实现

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该系统运用协同过滤推荐算法,通过综合分析旅游景点的用户评分数据和用户间的相似性,利用协同过滤算法来推荐旅游景点.算法考虑用户对其他景点的评分和偏好,结合相似用户的行为模式,从而为用户提供个性化的旅游景点推荐.同时利用Echarts框架提供的可视化图表、地图等,直观地展示用户评分和景点的推荐情况,节约用户的时间,提供良好的用户体验;系统后端采用Spring Boot框架,前端则使用Vue和El-ement-UI框架开发.
Design and Implementation of Visual Analysis System for Tourist Attrac-tions Based on Collaborative Filtering Algorithm
With the promotion of digital reform and digital economy,digital transformation ena-bles tourism enterprises to collect and analyze a large amount of data,thereby better understand-ing consumer needs and preferences.Tourists can also obtain better tourism experiences through big data analysis.This system uses collaborative filtering recommendation algorithms to compre-hensively analyze user rating data and similarity between users of tourist attractions,and uses collaborative filtering algorithms to recommend tourist attractions.The algorithm considers the user's ratings and preferences for other attractions,combined with similar user behavior pat-terns,to provide personalized tourist attraction recommendations for users.At the same time,u-tilizing the visualization charts,maps,etc.provided by the Echarts framework to visually display user ratings and recommended attractions,saving users time and providing a good user experi-ence;The backend of the system adopts the Spring Boot framework,while the frontend is devel-oped using Vue and Element UI frameworks.

AlgorithmCollaborative filtering,recommendation

张名扬、王子俊、罗兴稳、陈茂华

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西北民族大学,甘肃 兰州 730030

沧州交通学院,河北沧州 061100

江苏海洋大学,江苏连云港 222000

算法 协同过滤 推荐

2024

长江信息通信
湖北通信服务公司

长江信息通信

影响因子:0.338
ISSN:2096-9759
年,卷(期):2024.37(7)
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