融合用户长短期偏好的下一个兴趣点推荐方法A next point-of-interest recommendation method fusing users' long- and short-term preferences
钱浩墉,徐胜华,王琢璐,虞赢赢,叶欣宇
摘要(Abstract):
针对现有下一个兴趣点推荐方法过度依赖于轨迹会话的时间远近划分用户长短期偏好,以及短期偏好难以捕捉的问题,本文提出融合用户长短期偏好的下一个兴趣点推荐方法。该方法构建双层级耦合表征模块,以强化语义意图与实体选择之间的耦合关系;设计图谱域双频偏好解耦模块,利用双通道切比雪夫谱卷积,将低频分量建模为长期偏好,高频分量建模为短期偏好,在频域上实现了用户长短期偏好的建模,并引入跨层注意力机制实现语义引导实体的过程;构建全局空间拓扑增强模块,捕捉地理实体的高阶空间拓扑关系。实验结果表明,本文方法在纽约和东京两个公开数据集上的各项评价指标均优于主流方法。
关键词(KeyWords): 下一个兴趣点推荐;位置社交网络;长短期偏好建模;注意力机制;切比雪夫多项式
基金项目(Foundation): 国家自然科学基金项目(42371478)
作者(Author): 钱浩墉,徐胜华,王琢璐,虞赢赢,叶欣宇
DOI: 10.16251/j.cnki.1009-2307.2026.11.013
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