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基于Scrapy爬虫技术和图神经网络的生态旅游推荐技术

Ecotourism recommendation technology based on Scrapy crawler technology and graph neural network
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摘要 对基于Scrapy爬虫技术和图神经网络的生态旅游推荐技术进行研究,设计了一种融合图神经网络与注意力机制的生态旅游推荐系统,并采用Scrapy爬虫技术建立数据集对系统进行测试与验证。首先,对系统整体框架进行设计,其次对基本算法进行选择,并对用户偏好模型、生态旅游项目交互关系、属性关系模型以及评分预测模型进行搭建,最终获取综合推荐结果。最后对系统进行实验测试。实验结果表明:本研究的推荐系统的MAE与RMSE值最低,与基于Graphrec算法的推荐系统相比,MAE值提高了3.274%,RMSE值提高了3.124%,证明本研究的推荐系统适用于生态旅游项目推荐,且推荐效果良好。 In this paper,the ecotourism recommendation technology based on Scrapy crawler technology and graph neural network is studied,an ecotourism recommendation system integrating graph neural network and attention mechanism is designed,and the data set is established by using Scrapy crawler technology to test and verify the system.Firstly,the overall framework of the system is designed,the basic algorithm is selected,and the user preference model,the interaction relationship of ecotourism projects,the attribute relationship model and the scoring prediction model are constructed,and finally the comprehensive recommendation results are obtained.Finally,the system is experimentally tested.The experimental results show that the MAE and RMSE values of the recommendation system in this study are the lowest,and compared with the recommendation system based on Graphrec algorithm,the MAE value is increased by 3.274%,and the RMSE value is increased by 3.124%,which proves that the recommendation system in this study is suitable for ecotourism project recommendation and has good recommendation effect.
作者 张一恒 王芹 刁炜卿 王小静 ZHANG Yiheng;WANG Qin;DIAO Weiqing;WANG Xiaojing(Xi’an Siyuan University,Xi’an 710038,China)
机构地区 西安思源学院
出处 《自动化与仪器仪表》 2024年第2期6-10,共5页 Automation & Instrumentation
基金 2022年度西安市社科规划基金项目《城市更新背景下西安历史文化街区管理水平提升研究》(22GL58)。
关键词 Scrapy爬虫技术 生态旅游 图神经网络 注意力机制 推荐系统 scrapy crawler technology ecotourism graph neural networks attention mechanisms referral system
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