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pro vyhledávání: '"Shen, Tingjia"'
Sequential recommendation has attracted increasing attention due to its ability to accurately capture the dynamic changes in user interests. We have noticed that generative models, especially diffusion models, which have achieved significant results
Externí odkaz:
http://arxiv.org/abs/2409.10522
Autor:
Shen, Tingjia, Wang, Hao, Zhang, Jiaqing, Zhao, Sirui, Li, Liangyue, Chen, Zulong, Lian, Defu, Chen, Enhong
Cross-Domain Sequential Recommendation (CDSR) aims to mine and transfer users' sequential preferences across different domains to alleviate the long-standing cold-start issue. Traditional CDSR models capture collaborative information through user and
Externí odkaz:
http://arxiv.org/abs/2406.03085
Autor:
Wu, Likang, Zheng, Zhi, Qiu, Zhaopeng, Wang, Hao, Gu, Hongchao, Shen, Tingjia, Qin, Chuan, Zhu, Chen, Zhu, Hengshu, Liu, Qi, Xiong, Hui, Chen, Enhong
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive amounts of dat
Externí odkaz:
http://arxiv.org/abs/2305.19860
Akademický článek
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