老鼠系领带
发表于 2025-3-21 18:50:19
书目名称Web-Age Information Management影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK1021727<br><br> <br><br>书目名称Web-Age Information Management读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK1021727<br><br> <br><br>
猜忌
发表于 2025-3-21 20:48:29
https://doi.org/10.1007/978-3-319-39937-9cloud computing; distributed system; internet of things; semantic network; active learning; algorithm; cro
重叠
发表于 2025-3-22 02:35:16
Bin Cui,Nan Zhang,Dexi LiuIncludes supplementary material:
Excise
发表于 2025-3-22 06:05:50
978-3-319-39936-2Springer International Publishing Switzerland 2016
赏心悦目
发表于 2025-3-22 09:06:22
Web-Age Information Management978-3-319-39937-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
set598
发表于 2025-3-22 14:05:10
Discovering Underground Roads from Trajectories Without Road Network framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.
暗指
发表于 2025-3-22 19:22:00
Discovering Underground Roads from Trajectories Without Road Network framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.
不发音
发表于 2025-3-22 23:12:07
Point-of-Interest Recommendations by Unifying Multiple Correlationsnify different information in a framework and learn the exact function by using gradient descent methods. The experimental results on real-world data sets show that our recommendations are more effective than baseline methods.
Guileless
发表于 2025-3-23 02:55:09
Point-of-Interest Recommendations by Unifying Multiple Correlationsnify different information in a framework and learn the exact function by using gradient descent methods. The experimental results on real-world data sets show that our recommendations are more effective than baseline methods.
暂停,间歇
发表于 2025-3-23 09:21:16
http://reply.papertrans.cn/103/10218/1021727/1021727_10.png