rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Soft Computing for Knowledge Discovery and Data Mining
  name:
    name part: Maimon, Oded.
    role:
      role term: editor.
  name:
    name part: Rokach, Lior.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XIII, 433 p. online resource.
  abstract: Data mining is the science and technology of exploring large and complex bodies of data in order to discover useful and insightful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. Soft Computing for Knowledge Discovery and Data Mining introduces theoretical approaches and practical computing methods extending the envelope of problems that data mining can solve efficiently. From the editors of the leading Data Mining and Knowledge Discovery Handbook, 2005, this volume, by highly regarded authors, includes selected contributors of the Handbook. The first three parts of this book are devoted to the principal constituents of soft computing: neural networks, evolutionary algorithms and fuzzy logic. The last part compiles the recent advances in soft computing for data mining, such as swarm intelligence, diffusion process and agent technology. This book was written to provide investigators in the fields of information systems, engineering, computer science, operations research, bio-informatics, statistics and management with a profound source for the role of soft computing in data mining. Not only does this book feature illustrations of various applications including marketing, manufacturing, medical, and others, but it also includes various real-world case studies with detailed results. Soft Computing for Knowledge Discovery and Data Mining is designed for theoreticians, researchers and advanced practitioners in industry. Practitioners may be particularly interested in the description of real world data mining projects performed with soft computing. This book is also suitable as a textbook or reference for advanced-level students in mathematical quantitative methods in the above fields. About the editors: Oded Maimon is Full Professor at the Department of Industrial Engineering, Tel-Aviv University, Israel. Lior Rokach is Assistant Professor at the Department of Information System Engineering, Ben-Gu…
  table of contents: Neural Network Methods -- to Soft Computing for Knowledge Discovery and Data Mining -- Neural Networks For Data Mining -- Improved SOM Labeling Methodology for Data Mining Applications -- Evolutionary Methods -- A Review of evolutionary Algorithms for Data Mining -- Genetic Clustering for Data Mining -- Discovering New Rule Induction Algorithms with Grammar-based Genetic Programming -- evolutionary Design of Code-matrices for Multiclass Problems -- Fuzzy Logic Methods -- The Role of Fuzzy Sets in Data Mining -- Support Vector Machines and Fuzzy Systems -- KDD in Marketing with Genetic Fuzzy Systems -- Knowledge Discovery in a Framework for Modelling with Words -- Advanced Soft Computing Methods and Areas -- Swarm Intelligence Algorithms for Data Clustering -- A Diffusion Framework for Dimensionality Reduction -- Data Mining and Agent Technology: a fruitful symbiosis -- Approximate Frequent Itemset Mining In the Presence of Random Noise -- The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining.
  note: edited by Oded Maimon, Lior Rokach.
  subject:
    topic: Computer science
  subject:
    topic: Computer communication systems
  subject:
    topic: Database management
  subject:
    topic: Data mining
  subject:
    topic: Information storage and retrieval
  subject:
    topic: Artificial intelligence
  subject:
    topic: Pattern recognition
  subject:
    topic: Computer Science
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Database Management
  subject:
    topic: Information Storage and Retrieval
  subject:
    topic: Pattern Recognition
  subject:
    topic: Computer Communication Networks
  classification: Q334-342
  classification: TJ210.2-211.495
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  identifier: 9780387699356
  identifier: http://dx.doi.org/10.1007/978-0-387-69935-6
  record info:
    record creation date: 100301
    record change date: 20151204163309.0
    record identifier: 978-0-387-69935-6