Leveraging Two Types of Global Graph for Sequential Fashion Recommendation

Author:

Ding Yujuan1,Ma Yunshan2,Wong Wai Keung3,Chua Tat-Seng2

Affiliation:

1. Shenzhen University, Shenzhen, China

2. National University of Singapore, Singapore, Singapore

3. The Hong Kong Polytechnic University, Hong Kong, Hong Kong

Funder

Natural Science Foundation of China

Shenzhen Municipal Science and Technology Innovation Council

Guangdong Natural Science Foundation

Publisher

ACM

Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Graph-enhanced Knowledge Transfer Learning for Fashion Sequential Recommendation;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

2. Large Language Models for Graph Learning;Companion Proceedings of the ACM Web Conference 2024;2024-05-13

3. Disentangle interest trend and diversity for sequential recommendation;Information Processing & Management;2024-05

4. MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation;ACM Transactions on Information Systems;2024-03-22

5. Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction;Proceedings of the 17th ACM International Conference on Web Search and Data Mining;2024-03-04

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