Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)

Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
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DOI：
10.1145/3523227.3546767
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发表时间：
2022-03
期刊：
Proceedings of the 16th ACM Conference on Recommender Systems
影响因子：
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通讯作者：
Shijie Geng;Shuchang Liu;Zuohui Fu;Yingqiang Ge;Yongfeng Zhang
Shijie Geng;Shuchang Liu;Zuohui Fu;Yingqiang Ge;Yongfeng Zhang
中科院分区：
其他
文献类型：
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作者：
Shijie Geng;Shuchang Liu;Zuohui Fu;Yingqiang Ge;Yongfeng Zhang

文献摘要

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长期以来，不同的推荐任务需要设计特定于任务的架构和培训目标。因此，很难将知识和表示从一个任务转移到另一个任务，从而限制了泛化能力。
For a long time, different recommendation tasks require designing task-specific architectures and training objectives. As a result, it is hard to transfer the knowledge and representations from one task to another, thus restricting the generalization abil