Journal of Graphics ›› 2025, Vol. 46 ›› Issue (5): 1050-1060.DOI: 10.11996/JG.j.2095-302X.2025051050
• Computer Graphics and Virtual Reality • Previous Articles Next Articles
ZUO Yuqi1(), ZHANG Yunfeng1(
), ZHANG Qiuyue2, XU Yingcheng3
Received:
2024-08-22
Accepted:
2024-12-25
Online:
2025-10-30
Published:
2025-09-10
Contact:
ZHANG Yunfeng
About author:
First author contact:ZUO Yuqi (1998-), master student. Her main research interest covers recommendation algorithm. E-mail:yqzuo@mail.sdufe.edu.cn
Supported by:
CLC Number:
ZUO Yuqi, ZHANG Yunfeng, ZHANG Qiuyue, XU Yingcheng. Knowledge-aware recommendation based on hypergraph representation learning and Transformer model optimization[J]. Journal of Graphics, 2025, 46(5): 1050-1060.
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URL: http://www.txxb.com.cn/EN/10.11996/JG.j.2095-302X.2025051050
分类 | 具体项 | Book-Crossing | MovieLens-1M | Last.FM |
---|---|---|---|---|
用户-项目交互 | #用户 | 17860 | 6036 | 1872 |
#项目 | 14967 | 2445 | 3846 | |
#交互 | 139746 | 753772 | 42346 | |
知识图谱 | #实体 | 77903 | 182011 | 9366 |
#关系 | 25 | 12 | 60 | |
#元组 | 151500 | 1241996 | 15518 | |
超参数设置 | #迭代次数 | 1000 | 1000 | 1000 |
#嵌入向量维数 | 64 | 64 | 64 | |
#超边数 | 128 | 128 | 128 | |
#学习率 | 0.005 0 | 0.010 0 | 0.000 1 |
Table 1 Basic data of data sets, knowledge graphs, and hyperparameters
分类 | 具体项 | Book-Crossing | MovieLens-1M | Last.FM |
---|---|---|---|---|
用户-项目交互 | #用户 | 17860 | 6036 | 1872 |
#项目 | 14967 | 2445 | 3846 | |
#交互 | 139746 | 753772 | 42346 | |
知识图谱 | #实体 | 77903 | 182011 | 9366 |
#关系 | 25 | 12 | 60 | |
#元组 | 151500 | 1241996 | 15518 | |
超参数设置 | #迭代次数 | 1000 | 1000 | 1000 |
#嵌入向量维数 | 64 | 64 | 64 | |
#超边数 | 128 | 128 | 128 | |
#学习率 | 0.005 0 | 0.010 0 | 0.000 1 |
方法 | Book-Crossing | MovieLens-1M | Last.FM | |||
---|---|---|---|---|---|---|
AUC | F1 | AUC | F1 | AUC | F1 | |
BPRFM[ | 0.649 3 | 0.610 8 | 0.883 8 | 0.789 3 | 0.713 4 | 0.640 6 |
CKE[ | 0.675 6 | 0.620 2 | 0.900 8 | 0.797 2 | 0.721 6 | 0.643 1 |
RippleNet[ | 0.719 1 | 0.645 0 | 0.911 5 | 0.827 1 | 0.770 2 | 0.694 8 |
KGCN[ | 0.682 1 | 0.629 3 | 0.907 8 | 0.831 0 | 0.757 9 | 0.701 9 |
KGIN[ | 0.721 5 | 0.661 9 | 0.912 5 | 0.841 3 | 0.808 1 | 0.731 3 |
HGNN[ | 0.708 5 | 0.672 9 | 0.933 8 | 0.852 7 | 0.838 2 | 0.753 6 |
HCCF[ | 0.722 6 | 0.680 9 | 0.932 7 | 0.847 4 | 0.854 6 | 0.765 2 |
EFBH[ | 0.733 3 | 0.683 2 | 0.934 9 | 0.848 3 | 0.860 1 | 0.786 9 |
HC-CRKG[ | 0.752 6 | 0.682 9 | 0.945 0 | 0.872 0 | 0.886 0 | 0.798 0 |
HTKR(本文) | 0.759 4 | 0.694 2 | 0.957 9 | 0.895 4 | 0.862 8 | 0.794 7 |
Table 2 The results of AUC and F1 were compared
方法 | Book-Crossing | MovieLens-1M | Last.FM | |||
---|---|---|---|---|---|---|
AUC | F1 | AUC | F1 | AUC | F1 | |
BPRFM[ | 0.649 3 | 0.610 8 | 0.883 8 | 0.789 3 | 0.713 4 | 0.640 6 |
CKE[ | 0.675 6 | 0.620 2 | 0.900 8 | 0.797 2 | 0.721 6 | 0.643 1 |
RippleNet[ | 0.719 1 | 0.645 0 | 0.911 5 | 0.827 1 | 0.770 2 | 0.694 8 |
KGCN[ | 0.682 1 | 0.629 3 | 0.907 8 | 0.831 0 | 0.757 9 | 0.701 9 |
KGIN[ | 0.721 5 | 0.661 9 | 0.912 5 | 0.841 3 | 0.808 1 | 0.731 3 |
HGNN[ | 0.708 5 | 0.672 9 | 0.933 8 | 0.852 7 | 0.838 2 | 0.753 6 |
HCCF[ | 0.722 6 | 0.680 9 | 0.932 7 | 0.847 4 | 0.854 6 | 0.765 2 |
EFBH[ | 0.733 3 | 0.683 2 | 0.934 9 | 0.848 3 | 0.860 1 | 0.786 9 |
HC-CRKG[ | 0.752 6 | 0.682 9 | 0.945 0 | 0.872 0 | 0.886 0 | 0.798 0 |
HTKR(本文) | 0.759 4 | 0.694 2 | 0.957 9 | 0.895 4 | 0.862 8 | 0.794 7 |
方法 | Book-Crossing | MovieLens-1M | Last.FM | |||
---|---|---|---|---|---|---|
AUC | F1 | AUC | F1 | AUC | F1 | |
HTKR | 0.759 4 | 0.694 2 | 0.957 9 | 0.895 4 | 0.862 8 | 0.794 7 |
HTKR-全局超图 | 0.706 3 | 0.658 6 | 0.907 3 | 0.853 0 | 0.821 6 | 0.753 8 |
HTKR-非全局超图 | 0.718 6 | 0.678 2 | 0.916 0 | 0.875 3 | 0.844 5 | 0.776 5 |
HTKR-Transformer | 0.718 8 | 0.669 7 | 0.922 7 | 0.889 1 | 0.829 5 | 0.779 6 |
HTKR-超图-Transformer | 0.647 9 | 0.628 5 | 0.803 5 | 0.740 3 | 0.731 9 | 0.700 1 |
HTKR+10%噪声 | 0.760 7 | 0.702 2 | 0.959 8 | 0.899 1 | 0.867 9 | 0.805 4 |
HTKR+20%噪声 | 0.767 3 | 0.708 5 | 0.958 2 | 0.899 3 | 0.880 1 | 0.808 6 |
HTKR+50%噪声 | 0.624 7 | 0.640 8 | 0.914 0 | 0.811 9 | 0.754 6 | 0.701 2 |
Table 3 Results of ablation experiment
方法 | Book-Crossing | MovieLens-1M | Last.FM | |||
---|---|---|---|---|---|---|
AUC | F1 | AUC | F1 | AUC | F1 | |
HTKR | 0.759 4 | 0.694 2 | 0.957 9 | 0.895 4 | 0.862 8 | 0.794 7 |
HTKR-全局超图 | 0.706 3 | 0.658 6 | 0.907 3 | 0.853 0 | 0.821 6 | 0.753 8 |
HTKR-非全局超图 | 0.718 6 | 0.678 2 | 0.916 0 | 0.875 3 | 0.844 5 | 0.776 5 |
HTKR-Transformer | 0.718 8 | 0.669 7 | 0.922 7 | 0.889 1 | 0.829 5 | 0.779 6 |
HTKR-超图-Transformer | 0.647 9 | 0.628 5 | 0.803 5 | 0.740 3 | 0.731 9 | 0.700 1 |
HTKR+10%噪声 | 0.760 7 | 0.702 2 | 0.959 8 | 0.899 1 | 0.867 9 | 0.805 4 |
HTKR+20%噪声 | 0.767 3 | 0.708 5 | 0.958 2 | 0.899 3 | 0.880 1 | 0.808 6 |
HTKR+50%噪声 | 0.624 7 | 0.640 8 | 0.914 0 | 0.811 9 | 0.754 6 | 0.701 2 |
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