自动化与仪器仪表2024,Issue(2) :6-10.DOI:10.14016/j.cnki.1001-9227.2024.02.006

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

张一恒 王芹 刁炜卿 王小静
自动化与仪器仪表2024,Issue(2) :6-10.DOI:10.14016/j.cnki.1001-9227.2024.02.006

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

张一恒 1王芹 1刁炜卿 1王小静1
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作者信息

  • 1. 西安思源学院,西安 710038
  • 折叠

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.

Abstract

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 de-signed,the basic algorithm is selected,and the user preference model,the interaction relationship of ecotourism projects,the attrib-ute relationship model and the scoring prediction model are constructed,and finally the comprehensive recommendation results are ob-tained.Finally,the system is experimentally tested.The experimental results show that the MAE and RMSE values of the recommen-dation system in this study are the lowest,and compared with the recommendation system based on Graphrec algorithm,the MAE val-ue 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.

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

Key words

scrapy crawler technology/ecotourism/graph neural networks/attention mechanisms/referral system

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基金项目

西安市社会科学基金规划项目(2022)(22GL58)

出版年

2024
自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子:0.327
ISSN:1001-9227
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