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Advanced Data Mining and Applications : 5th International Conference, ADMA 2009, Beijing, China, August 17-19, 2009. Proceedings / edited by Ronghuai Huang, Qiang Yang, Jian Pei, João Gama, Xiaofeng Meng, Xue Li.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Lecture Notes in Computer Science ; 5678Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009Descripción: recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783642033483
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA76.9.D343
Recursos en línea:
Contenidos:
Keynotes -- Regular Papers -- Short Papers.
Resumen: This book constitutes the refereed proceedings of the 5th International Conference on Advanced Data Mining and Applications, ADMA 2009, held in Beijing, China, in August 2009. The 34 revised full papers and 47 revised short papers presented together with the abstract of 4 keynote lectures were carefully reviewed and selected from 322 submissions from 27 countries. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.
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Springer eBooks

Keynotes -- Regular Papers -- Short Papers.

This book constitutes the refereed proceedings of the 5th International Conference on Advanced Data Mining and Applications, ADMA 2009, held in Beijing, China, in August 2009. The 34 revised full papers and 47 revised short papers presented together with the abstract of 4 keynote lectures were carefully reviewed and selected from 322 submissions from 27 countries. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.

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