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Titlebook: Advanced Data Mining and Applications; 10th International C Xudong Luo,Jeffrey Xu Yu,Zhi Li Conference proceedings 2014 Springer Internatio

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發(fā)表于 2025-3-21 16:04:48 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Advanced Data Mining and Applications
期刊簡稱10th International C
影響因子2023Xudong Luo,Jeffrey Xu Yu,Zhi Li
視頻videohttp://file.papertrans.cn/146/145487/145487.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advanced Data Mining and Applications; 10th International C Xudong Luo,Jeffrey Xu Yu,Zhi Li Conference proceedings 2014 Springer Internatio
影響因子This book constitutes the proceedings of the 10th International Conference on Advanced Data Mining and Applications, ADMA 2014, held in Guilin, 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, advance machine learning techniques, classification, big data and applications, clustering methods, machine learning, and data mining and database.
Pindex Conference proceedings 2014
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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
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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
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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
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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.
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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.
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