Advances in Knowledge Discovery and Data Mining: 12th Pacific-Asia Conference, PAKDD 2008 Osaka, Japan, May 20-23, 2008 Proceedings: Lecture Notes in Computer Science, cartea 5012
Editat de Takashi Washio, Einoshin Suzuki, Kai Ming Ting, Akihiro Inokuchien Limba Engleză Paperback – 8 mai 2008
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Specificații
ISBN-13: 9783540681243
ISBN-10: 3540681248
Pagini: 1132
Ilustrații: XXIV, 1102 p.
Dimensiuni: 155 x 235 x 41 mm
Greutate: 1.25 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3540681248
Pagini: 1132
Ilustrații: XXIV, 1102 p.
Dimensiuni: 155 x 235 x 41 mm
Greutate: 1.25 kg
Ediția:2008
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Keynote Speech.- Invited Speeches.- Long Papers.- Regular Papers.- Short Papers.
Textul de pe ultima copertă
This book constitutes the refereed proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2008, held in Osaka, Japan, in May 2008.
The 37 revised long papers, 40 revised full papers, and 36 revised short papers presented together with 1 keynote talk and 4 invited lectures were carefully reviewed and selected from 312 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.
The 37 revised long papers, 40 revised full papers, and 36 revised short papers presented together with 1 keynote talk and 4 invited lectures were carefully reviewed and selected from 312 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction, and knowledge-based systems.