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With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
Engineering sciences. Technology --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- ICT (informatie- en communicatietechnieken) --- analyse (wiskunde) --- data mining --- informatiesystemen --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- robots --- AI (artificiële intelligentie)
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Biomathematics. Biometry. Biostatistics --- General ecology and biosociology --- Computer science --- Information systems --- biodiversiteit --- bio-informatica --- informatica --- biometrie --- database management
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The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data. For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science. .
Ergodic theory. Information theory --- Mathematical control systems --- Mathematics --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- coderen --- toegepaste wiskunde --- datamining --- wiskunde --- gegevensanalyse --- KI (kunstmatige intelligentie) --- data acquisition --- informatietheorie --- AI (artificiële intelligentie)
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