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Intelligent Text Categorization and Clustering: Studies in Computational Intelligence, cartea 164

Editat de Felipe M. G. França, Alberto Ferreira de Souza
en Limba Engleză Hardback – oct 2008
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.
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Specificații

ISBN-13: 9783540856436
ISBN-10: 3540856439
Pagini: 136
Ilustrații: XIV, 120 p. 34 illus.
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.32 kg
Ediția:2009
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

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.

Textul de pe ultima copertă

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.

Caracteristici

Recent advances in Text Categorization and Clustering