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pro vyhledávání: '"Chen, Gaode"'
Autor:
Luo, Yunze, Jiang, Yuezihan, Jiang, Yinjie, Chen, Gaode, Wang, Jingchi, Bian, Kaigui, Li, Peiyi, Zhang, Qi
With the rise of e-commerce and short videos, online recommender systems that can capture users' interests and update new items in real-time play an increasingly important role. In both online and offline recommendation, the cold-start problem due to
Externí odkaz:
http://arxiv.org/abs/2411.11225
In addressing the persistent challenges of data-sparsity and cold-start issues in domain-expert recommender systems, Cross-Domain Recommendation (CDR) emerges as a promising methodology. CDR aims at enhancing prediction performance in the target doma
Externí odkaz:
http://arxiv.org/abs/2409.04540
Autor:
Chen, Gaode, Su, Yijun, Zhang, Xinghua, Hu, Anmin, Chen, Guochun, Feng, Siyuan, Xiang, Ji, Zhang, Junbo, Zheng, Yu
Data insufficiency problems (i.e., data missing and label scarcity) caused by inadequate services and infrastructures or imbalanced development levels of cities have seriously affected the urban computing tasks in real scenarios. Prior transfer learn
Externí odkaz:
http://arxiv.org/abs/2206.00007
Sequential recommendation systems alleviate the problem of information overload, and have attracted increasing attention in the literature. Most prior works usually obtain an overall representation based on the user's behavior sequence, which can not
Externí odkaz:
http://arxiv.org/abs/2106.04415
Autor:
Feng, Siyuan, Wei, Shuqing, Zhang, Junbo, Li, Yexin, Ke, Jintao, Chen, Gaode, Zheng, Yu, Yang, Hai
Publikováno v:
In Transportation Research Part C November 2023 156
