MELT: 面向序列推荐的长尾用户和项目相互增强（英文版）

英文标题：MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation中文摘要：本文提出了基于互补学习和课程学习的新框架 Mutual Enhancement of Long-Tailed user and item (MELT)，它是序列推荐系统中第一篇同时解决长尾用户和物品的问题，同时也是模型无关的。实验结果表明，该方法可以有效地缓解长尾问题，并且不会牺牲头部用户和物品的性能。英文摘要：The long-tailed problem is a long-standing challenge in SequentialRecommender Systems (SRS) in which the problem exists in terms of both usersand items. While many existing studies address the long-tailed problem in SRS,they only focus on either the