TY  - BOOK
AU  - Nedjah,Nadia
AU  - Macedo Mourelle,Luiza de
AU  - Kacprzyk,Janusz
AU  - França,Felipe M.G.
AU  - De Souza,Alberto Ferreira de
ED  - SpringerLink (Online service)
TI  - Intelligent Text Categorization and Clustering
T2  - Studies in Computational Intelligence,
SN  - 9783540856443
AV  - TA329-348 
U1  - 519 23
PY  - 2009///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Engineering
KW  - Artificial intelligence
KW  - Text processing (Computer science)
KW  - Computational linguistics
KW  - Applied mathematics
KW  - Engineering mathematics
KW  - Appl.Mathematics/Computational Methods of Engineering
KW  - Artificial Intelligence (incl. Robotics)
KW  - Computational Linguistics
KW  - Document Preparation and Text Processing
KW  - Language Translation and Linguistics
KW  - Electronic books
KW  - local
N1  - 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
N2  - 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
UR  - http://ezproxy.alfaisal.edu/login?url=http://dx.doi.org/10.1007/978-3-540-85644-3
ER  -