Titlebook: Advances in Knowledge Discovery and Data Mining; 7th Pacific-Asia Con Kyu-Young Whang,Jongwoo Jeon,Jaideep Srivastava Conference proceeding

JADE

書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)




書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)學科排名




書目名稱Advances in Knowledge Discovery and Data Mining網絡公開度




書目名稱Advances in Knowledge Discovery and Data Mining網絡公開度學科排名




書目名稱Advances in Knowledge Discovery and Data Mining被引頻次




書目名稱Advances in Knowledge Discovery and Data Mining被引頻次學科排名




書目名稱Advances in Knowledge Discovery and Data Mining年度引用




書目名稱Advances in Knowledge Discovery and Data Mining年度引用學科排名




書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋




書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋學科排名

Cloudburst

978-3-540-04760-5Springer-Verlag Berlin Heidelberg 2003

recession

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/148644.jpg

dilute

RALES

https://doi.org/10.1007/978-3-540-34719-4 needs of these industrial and business specific applications. However, there are still considerable challenges facing this multidisciplinary field. Drawing from some industry specific applications this talk will cover the trends and challenges facing the researchers and practitioners of this rapidl

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constitutional

昆蟲

https://doi.org/10.1007/978-3-540-34719-4d another variation in this family — K-Harmonic Means (KHM). It has been demonstrated using a small number of “benchmark” datasets that KHM is more robust than K-means and EM. In this paper, we compare their performance statistically. We run K-means, K-Harmonic Means and EM on each of 3600 pairs of

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