New Frontiers in Applied Data Mining PAKDD 2009 International Workshops, Bangkok, Thailand, April 27-30, 2010. Revised Selected Papers /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Theeramunkong, Thanaruk (Editor ), Nattee, Cholwich (Editor ), Adeodato, Paulo J. L. (Editor ), Chawla, Nitesh (Editor ), Christen, Peter (Editor ), Lenca, Philippe (Editor ), Poon, Josiah (Editor ), Williams, Graham (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Lecture Notes in Artificial Intelligence, 5669
Temas:
Artificial intelligence.
Database management.
Information storage and retrieval systems.
Application software.
Data mining.
Pattern recognition systems.
Artificial Intelligence.
Database Management.
Information Storage and Retrieval.
Computer and Information Systems Applications.
Data Mining and Knowledge Discovery.
Automated Pattern Recognition.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • The iZi Project: Easy Prototyping of Interesting Pattern Mining Algorithms
  • CODE: A Data Complexity Framework for Imbalanced Datasets
  • An Empirical Study of Applying Ensembles of Heterogeneous Classifiers on Imperfect Data
  • Undersampling Approach for Imbalanced Training Sets and Induction from Multi-label Text-Categorization Domains
  • Adaptive Methods for Classification in Arbitrarily Imbalanced and Drifting Data Streams
  • Two Measures of Objective Novelty in Association Rule Mining
  • PAKDD Data Mining Competition 2009: New Ways of Using Known Methods
  • Feature Selection for Brain-Computer Interfaces
  • Mining Protein Interactions from Text Using Convolution Kernels
  • Missing Phrase Recovering by Combining Forward and Backward Phrase Translation Tables
  • Automatic Extraction of Thai-English Term Translations and Synonyms from Medical Web using Iterative Candidate Generation with Association Measures
  • Accurate Subsequence Matching on Data Stream under Time Warping Distance.

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