基于图神经网络的兴趣点推荐方法研究进展

方金凤; 陈祖颐

doi:10.3981/j.issn.1000-7857.2024.01.00099

科技导报 >

2025 , Vol. 43 >Issue 9: 76 - 83

DOI: https://doi.org/10.3981/j.issn.1000-7857.2024.01.00099

研究论文

基于图神经网络的兴趣点推荐方法研究进展

方金凤 ,
陈祖颐

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辽宁工程技术大学电子与信息工程学院, 葫芦岛 125105

方金凤，讲师，研究方向为时空大数据、兴趣点推荐、轨迹预测等，电子信箱：lnfangziyi@163.com

收稿日期: 2024-01-05

网络出版日期: 2025-06-13

基金资助

辽宁省教育厅理工类项目(JYTQN2023211)

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Research progress on point-of-interest recommendation methods based on graph neural networks

Jinfeng FANG ,
Zuyi CHEN

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School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, China

Received date: 2024-01-05

Online published: 2025-06-13

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摘要

交叉学科是新科学的生长点，是科学发展的必然趋势。基于位置服务的重要应用——兴趣点推荐，作为计算机学科与地理信息学科相交叉的研究课题，对于推动2个学科在时空数据分析等相关领域的交叉融合研究具有重要作用。分析了兴趣点推荐的影响因素即地理位置、时间因素、社交关系和流行度，重点阐述了基于图神经网络的兴趣点推荐方法，包括基于图注意力网络、图卷积网络、图自编码器的推荐，并对其特点进行对比；讨论了在兴趣点推荐中存在的一些关键挑战，如数据稀疏性、冷启动问题和用户动态偏好问题，并针对各项挑战提出相应的解决思路，提出了结合多种影响因素的推荐，跨领域推荐以及动态偏好推荐的发展趋势。

关键词： 兴趣点推荐; 基于位置的服务; 图神经网络; 推荐算法

本文引用格式

方金凤 , 陈祖颐 . 基于图神经网络的兴趣点推荐方法研究进展[J]. 科技导报, 2025 , 43(9) : 76 -83 . DOI: 10.3981/j.issn.1000-7857.2024.01.00099

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