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Título Intelligent Data Engineering and Automated Learning ́㠉DEAL 2014 [electronic resource] : 15th International Conference, Salamanca, Spain, September 10-12, 2014. Proceedings / edited by Emilio Corchado, José A. Lozano, Héctor Quintián, Hujun Yin.

Descripción física XX, 508 p. 147 illus. online resource.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Colección Lecture Notes in Computer Science, 0302-9743 ; 8669
Lecture Notes in Computer Science, 0302-9743 ; 8669
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Springer eBooks. Computer Science
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Resumen: This book constitutes the refereed proceedings of the 15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014, held in Salamanca, Spain, in September 2014. The 60 revised full papers presented were carefully reviewed and selected from about 120 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition the conference provided a good sample of current topics from methodologies, frameworks, and techniques to applications and case studies. The techniques include computational intelligence, big data analytics, social media techniques, multi-objective optimization, regression, classification, clustering, biological data processing, text processing, and image/video analysis.
Materia Computer science.
Computers.
Algorithms.
Data mining.
Information storage and retrieval.
Artificial intelligence.
Pattern recognition.
Computer Science.
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Data Mining and Knowledge Discovery.
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Pattern Recognition.
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Artificial Intelligence (incl. Robotics).
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Algorithm Analysis and Problem Complexity.
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Information Storage and Retrieval.
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Computation by Abstract Devices.
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Autor secundario Corchado, Emilio., editor.
Lozano, José A., editor.
Quintián, Héctor., editor.
Yin, Hujun., editor.
SpringerLink (Online service)
En Springer eBooks
OTRO SOPORTE Printed edition: 9783319108391
ISBN 9783319108407 978-3-319-10840-7
ISBN/ISSN 10.1007/978-3-319-10840-7 doi