使入伍
发表于 2025-3-21 17:12:06
书目名称Database Systems for Advanced Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0263402<br><br> <br><br>书目名称Database Systems for Advanced Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0263402<br><br> <br><br>
信徒
发表于 2025-3-21 23:08:58
0302-9743 D consortium papers are included. The conference presents papers on subjects such as model, graph, learning, performance, knowledge, time, recommendation, representation, attention, prediction, and network..978-3-031-30671-6978-3-031-30672-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
载货清单
发表于 2025-3-22 04:25:03
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压迫
发表于 2025-3-22 05:08:53
Who Is That Man? Lad Trouble in ,, and d information aggregation module to accurately learn item-level relation features from a knowledge graph. Extensive experiments conducted on three real-world datasets demonstrate the superiority of our KRec-C2 model over existing state-of-the-art methods.
极端的正确性
发表于 2025-3-22 09:04:33
KRec-C2: A Knowledge Graph Enhanced Recommendation with Context Awareness and Contrastive Learningd information aggregation module to accurately learn item-level relation features from a knowledge graph. Extensive experiments conducted on three real-world datasets demonstrate the superiority of our KRec-C2 model over existing state-of-the-art methods.
都相信我的话
发表于 2025-3-22 16:20:06
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都相信我的话
发表于 2025-3-22 18:49:07
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墙壁
发表于 2025-3-23 01:14:11
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Culmination
发表于 2025-3-23 04:19:35
Thompson Sampling with Time-Varying Reward for Contextual Banditsalgorithm. Extensive empirical experiments on two real-world datasets show that our proposed algorithm outperforms state-of-the-art time-varying bandit algorithms. Furthermore, the designed reward mechanism can be flexibly configured to other bandit algorithms to improve them.
善于
发表于 2025-3-23 09:08:33
Cold-Start Based Multi-scenario Ranking Model for Click-Through Rate Predictionn attention mechanism; and 2) User Representation Memory Network (URMN), which benefits cold-start users from users with rich behaviors through a memory read and write mechanism. CSMN seamlessly integrates both components in an end-to-end learning framework. Extensive experiments on real-world offli