Intelligent text categorization and clustering

Author(s)

Bibliographic Information

Intelligent text categorization and clustering

Nadia Nedjah ... [et al.] (eds.)

(Studies in computational intelligence, v. 164)

Springer, c2009

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Description and Table of Contents

Description

Automatic Text Categorization and Clustering are becoming more and more important as the amount of text in electronic format grows and the access to it becomes more necessary and widespread. Well known applications are spam filtering and web search, but a large number of everyday uses exist (intelligent web search, data mining, law enforcement, etc.) Currently, researchers are employing many intelligent techniques for text categorization and clustering, ranging from support vector machines and neural networks to Bayesian inference and algebraic methods, such as Latent Semantic Indexing. This volume offers a wide spectrum of research work developed for intelligent text categorization and clustering. In the following, we give a brief introduction of the chapters that are included in this book.

Table of Contents

Gene Selection from Microarray Data.- Preprocessing Techniques for Online Handwriting Recognition.- A Simple and Fast Term Selection Procedure for Text Clustering.- Bilingual Search Engine and Tutoring System Augmented with Query Expansion.- Comparing Clustering on Symbolic Data.- Exploring a Genetic Algorithm for Hypertext Documents Clustering.

by "Nielsen BookData"

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Details

  • NCID
    BA87546539
  • ISBN
    • 9783540856436
  • LCCN
    2008933299
  • Country Code
    gw
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Berlin
  • Pages/Volumes
    xiii, 117 p.
  • Size
    24 cm
  • Parent Bibliography ID
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