Intelligent Data Mining Techniques and Applications /

Intelligent Data Mining - Techniques and Applications is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main object...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Ruan, Da (Editor ), Chen, Guoqing (Editor ), Kerre, Etienne E. (Editor ), Wets, Geert (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005.
Edición:1st ed. 2005.
Colección:Studies in Computational Intelligence, 5
Temas:
Engineering mathematics.
Engineering-Data processing.
Pattern recognition systems.
Computer networks .
Business information services.
Control engineering.
Robotics.
Automation.
Mathematical and Computational Engineering Applications.
Automated Pattern Recognition.
Computer Communication Networks.
IT in Business.
Control, Robotics, Automation.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • From the contents: Part 1: Intelligent Systems and Data Mining; Some Considerations in Multi-Source Data Fusion; Granular Nested Causal Complexes; Gene Regulating Network Discovery; Semantic Relations and Information Discovery; Sequential Pattern Mining; Uncertain Knowledge Association through Information Gain; Data Mining for Maximal Frequency Patterns in Sequence Group; Mining Association Rule with Rough Sets; The Evolution of the Concept of Fuzzy Measure
  • Part 2: Economic and Management Applications; Building ER Models with Association Rules; Discovering the Factors Affecting the Location Selection of FDI in China; Penalty-Reward Analysis with Uninorms: A Study of Customer (Dis)Satisfaction
  • Part 3: Industrial Engineering Applications; Fuzzy Process Control with Intelligent Data Mining; Accelerating the New Product Introduction with Intelligent Data Mining; Integrated Clustering Modeling with Backpropagation Neural Network for Efficient Customer Relationship Management Mining.

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