genial 发表于 2025-3-21 17:28:45
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Yanliang Du,Baochen Sun,Jianzhi Li,Wentao Zhangsearch on group recommendation, which focuses on the issue of recommending items to a group of users. The existing methods on addressing the problem of grouping users and making recommendations for the formed groups simultaneously, however, often suffer from two defects. The first one is that they srefine 发表于 2025-3-22 05:48:51
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Yanliang Du,Baochen Sun,Jianzhi Li,Wentao Zhangreference attributes, etc. It’s a powerful data support of precision marketing. Existing methods mainly study network behavior, personal preferences and post texts to build user profile. Through our data analysis of micro-blog, we find that females show more positive and have richer sentiments than佛刊 发表于 2025-3-22 16:01:29
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Yanliang Du,Baochen Sun,Jianzhi Li,Wentao Zhangsearch on group recommendation, which focuses on the issue of recommending items to a group of users. The existing methods on addressing the problem of grouping users and making recommendations for the formed groups simultaneously, however, often suffer from two defects. The first one is that they sharangue 发表于 2025-3-23 00:05:45
Yanliang Du,Baochen Sun,Jianzhi Li,Wentao Zhangrevalence of big data applications, vast unstructured and semi-structured data are generated, deeply challenging the relational model used in RDBMSs. For this reason, a wide spectrum of NoSQL databases are developed for managing unstructured, semi-structured or structured data. For example, graph da让空气进入 发表于 2025-3-23 04:03:47
Yanliang Du,Baochen Sun,Jianzhi Li,Wentao Zhang and applications in both academic and industrial communities. However, the scalability of the conventional recommendation algorithms has been challenged by the exponential growth of the resource data size, and the increasing time span of the data also raises new requirements on the time-awareness o牌带来 发表于 2025-3-23 06:42:32
Yanliang Du,Baochen Sun,Jianzhi Li,Wentao Zhang and applications in both academic and industrial communities. However, the scalability of the conventional recommendation algorithms has been challenged by the exponential growth of the resource data size, and the increasing time span of the data also raises new requirements on the time-awareness o