橱柜 发表于 2025-3-21 16:04:48
书目名称Advanced Data Mining and Applications影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0145487<br><br> <br><br>书目名称Advanced Data Mining and Applications读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0145487<br><br> <br><br>绿州 发表于 2025-3-21 23:29:52
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0302-9743 in, China during December 2014. The 48 regular papers and 10 workshop papers presented in this volume were carefully reviewed and selected from 90 submissions. They deal with the following topics: data mining, social network and social media, recommend systems, database, dimensionality reduction, ad山羊 发表于 2025-3-22 18:24:53
Conference proceedings 2014during December 2014. The 48 regular papers and 10 workshop papers presented in this volume were carefully reviewed and selected from 90 submissions. They deal with the following topics: data mining, social network and social media, recommend systems, database, dimensionality reduction, advance mach凶兆 发表于 2025-3-22 21:36:58
0302-9743 vance machine learning techniques, classification, big data and applications, clustering methods, machine learning, and data mining and database.978-3-319-14716-1978-3-319-14717-8Series ISSN 0302-9743 Series E-ISSN 1611-3349歌唱队 发表于 2025-3-23 03:03:30
Seeing China: Shaw and His Contemporariesscovers HUIs without generating candidates and introduces several strategies to handle items with negative unit profits efficiently. Experimental results with six real-life datasets shows that FHN is up to 500 times faster and can use up to 250 times less memory than the state-of-the-art algorithm HUINIV-Mine.monopoly 发表于 2025-3-23 05:49:10
Bernard Shaw’s Bridges to Chinese Cultured . and . are proposed to respectively mine these representations. Experiments on both real and synthetic datasets show that proposed algorithms are very efficient and that these representations are up to 36 times smaller than the set of all HUIs.