Journal of Computer Applications ›› 2024, Vol. 44 ›› Issue (9): 2704-2710.DOI: 10.11772/j.issn.1001-9081.2023091264
• Data science and technology • Previous Articles Next Articles
Xingyao YANG1(), Yu CHEN1, Jiong YU1, Zulian ZHANG2, Jiaying CHEN1, Dongxiao WANG1
Received:
2023-09-14
Revised:
2023-10-26
Accepted:
2023-10-31
Online:
2023-11-23
Published:
2024-09-10
Contact:
Xingyao YANG
About author:
CHEN Yu, born in 2000, M. S. candidate. His research interests include recommender system.Supported by:
杨兴耀1(), 陈羽1, 于炯1, 张祖莲2, 陈嘉颖1, 王东晓1
通讯作者:
杨兴耀
作者简介:
杨兴耀(1984—),男,湖北襄阳人,副教授,博士,CCF会员,主要研究方向:推荐系统、大数据、信任计算基金资助:
CLC Number:
Xingyao YANG, Yu CHEN, Jiong YU, Zulian ZHANG, Jiaying CHEN, Dongxiao WANG. Recommendation model combining self-features and contrastive learning[J]. Journal of Computer Applications, 2024, 44(9): 2704-2710.
杨兴耀, 陈羽, 于炯, 张祖莲, 陈嘉颖, 王东晓. 结合自我特征和对比学习的推荐模型[J]. 《计算机应用》唯一官方网站, 2024, 44(9): 2704-2710.
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URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2023091264
数据集 | 用户数 | 项目数 | 交互数 | 稀疏度/% |
---|---|---|---|---|
ML-latest-small | 593 | 1 297 | 67 705 | 8.800 |
Last.FM | 1 892 | 17 632 | 92 834 | 0.280 |
Yelp | 42 712 | 26 822 | 182 357 | 0.016 |
Tab. 1 Statistics of experimental datasets
数据集 | 用户数 | 项目数 | 交互数 | 稀疏度/% |
---|---|---|---|---|
ML-latest-small | 593 | 1 297 | 67 705 | 8.800 |
Last.FM | 1 892 | 17 632 | 92 834 | 0.280 |
Yelp | 42 712 | 26 822 | 182 357 | 0.016 |
模型 | K | ML-latest-small | Last.FM | Yelp | |||
---|---|---|---|---|---|---|---|
R@K | N@K | R@K | N@K | R@K | N@K | ||
LightGCN | 20 | 0.250 5 | 0.195 4 | 0.234 9 | 0.170 4 | 0.076 1 | 0.037 3 |
NCL | 0.248 6 | 0.194 9 | 0.235 3 | 0.171 5 | |||
SimGCL | 0.225 7 | 0.182 4 | 0.238 0 | 0.176 2 | 0.078 8 | 0.039 5 | |
GraphDA | 0.079 7 | 0.037 6 | |||||
SfCLRec | 0.332 4 | 0.284 7 | 0.278 4 | 0.223 0 | 0.089 0 | 0.043 4 | |
LightGCN | 40 | 0.364 0 | 0.233 3 | 0.322 0 | 0.202 2 | 0.117 5 | 0.047 4 |
NCL | 0.384 0 | 0.235 4 | 0.325 2 | 0.203 3 | |||
SimGCL | 0.353 3 | 0.222 9 | 0.333 9 | 0.206 5 | 0.121 3 | 0.049 8 | |
GraphDA | 0.122 7 | 0.048 1 | |||||
SfCLRec | 0.444 6 | 0.315 4 | 0.373 7 | 0.255 6 | 0.133 9 | 0.054 5 |
Tab. 2 Experimental results of different models on three datasets
模型 | K | ML-latest-small | Last.FM | Yelp | |||
---|---|---|---|---|---|---|---|
R@K | N@K | R@K | N@K | R@K | N@K | ||
LightGCN | 20 | 0.250 5 | 0.195 4 | 0.234 9 | 0.170 4 | 0.076 1 | 0.037 3 |
NCL | 0.248 6 | 0.194 9 | 0.235 3 | 0.171 5 | |||
SimGCL | 0.225 7 | 0.182 4 | 0.238 0 | 0.176 2 | 0.078 8 | 0.039 5 | |
GraphDA | 0.079 7 | 0.037 6 | |||||
SfCLRec | 0.332 4 | 0.284 7 | 0.278 4 | 0.223 0 | 0.089 0 | 0.043 4 | |
LightGCN | 40 | 0.364 0 | 0.233 3 | 0.322 0 | 0.202 2 | 0.117 5 | 0.047 4 |
NCL | 0.384 0 | 0.235 4 | 0.325 2 | 0.203 3 | |||
SimGCL | 0.353 3 | 0.222 9 | 0.333 9 | 0.206 5 | 0.121 3 | 0.049 8 | |
GraphDA | 0.122 7 | 0.048 1 | |||||
SfCLRec | 0.444 6 | 0.315 4 | 0.373 7 | 0.255 6 | 0.133 9 | 0.054 5 |
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