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Basic Concepts of Data Stream Mining

  • Leszek RutkowskiEmail author
  • Maciej Jaworski
  • Piotr Duda
Chapter
Part of the Studies in Big Data book series (SBD, volume 56)

Abstract

Data stream mining, as its name suggests, is connected with two basic fields of computer science, i.e. data mining and data streams. Data mining [1, 2, 3, 4] is an interdisciplinary subfield of computer science whose main aim is to develop tools and methods for exploring knowledge from large datasets. Data mining is strictly related to statistics, pattern recognition [5] and machine learning [6], using methods like neural networks, decision trees, Bayesian networks or support vector machines. Neural networks are often considered a method belonging to soft computing or computational intelligence [7]. Another soft computing concept used in data mining is fuzzy logic. It should be noted that all mentioned above subfields of computer science are not strictly defined and overlap in many issues. Moreover, data mining is something more than learning or extracting knowledge, and includes, among others, database systems or data visualization as well. However, this book focuses mainly on the learning aspect of data mining.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Leszek Rutkowski
    • 1
    • 2
    Email author
  • Maciej Jaworski
    • 1
  • Piotr Duda
    • 1
  1. 1.Institute of Computational IntelligenceCzestochowa University of TechnologyCzęstochowaPoland
  2. 2.Information Technology InstituteUniversity of Social SciencesLodzPoland

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