GPT4Rec: Graph Prompt Tuning for Streaming Recommendation
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- GPT4Rec: Graph Prompt Tuning for Streaming Recommendation
Recommendations
Streaming Session-based Recommendation
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data MiningSession-based Recommendation (SR) is the task of recommending the next item based on previously recorded user interactions. In this work, we study SR in a practical streaming scenario, namely Streaming Session-based Recommendation (SSR), which is a more ...
Dynamically Expandable Graph Convolution for Streaming Recommendation
WWW '23: Proceedings of the ACM Web Conference 2023Personalized recommender systems have been widely studied and deployed to reduce information overload and satisfy users’ diverse needs. However, conventional recommendation models solely conduct a one-time training-test fashion and can hardly adapt to ...
Contrastive Graph Prompt-tuning for Cross-domain Recommendation
Recommender systems commonly suffer from the long-standing data sparsity problem where insufficient user-item interaction data limits the systems’ ability to make accurate recommendations. This problem can be alleviated using cross-domain recommendation ...
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- General Chairs:
- Grace Hui Yang,
- Hongning Wang,
- Sam Han,
- Program Chairs:
- Claudia Hauff,
- Guido Zuccon,
- Yi Zhang
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Association for Computing Machinery
New York, NY, United States
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- Natural Science Foundation of China
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