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Knowledge Discovery in Inductive Databases 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers (Lecture Notes in Computer Science)

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Published by Springer .
Written in English

Subjects:

  • Databases & data structures,
  • Computers,
  • Computers - Data Base Management,
  • Computer Books: Database,
  • Artificial Intelligence - General,
  • Database Management - General,
  • Computers / Database Management / General,
  • classification,
  • clustering,
  • constraint-based mining,
  • data management,
  • data mining,
  • inductive databases,
  • knowledge discovery,
  • machine learning,
  • multi-objective regression,
  • pattern mining,
  • query languages,
  • query optimization

Book details:

Edition Notes

ContributionsFrancesco Bonchi (Editor), Jean-Francois Boulicaut (Editor)
The Physical Object
FormatPaperback
Number of Pages251
ID Numbers
Open LibraryOL9056438M
ISBN 103540332928
ISBN 109783540332923

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Knowledge Discovery in Inductive Databases: 4th International Workshop, KDID , Porto, Portugal, October 3, , Revised Selected and Invited Papers (Lecture Notes in Computer Science ()) [Bonchi, Francesco, Boulicaut, Jean-Francois] on *FREE* shipping on qualifying offers. Knowledge Discovery in Inductive Databases: 4th International Workshop, . It spans many different approaches to discovery, including inductive learning, bayesian statistics, semantic query optimization, knowledge acquisition for expert systems, information theory, and fuzzy 1 rapid growth in the number and size of databases creates a need for tools and techniques for intelligent data : Paperback. Knowledge Discovery in Inductive Databases 5th International Workshop, KDID Berlin, Germany, Septem Revised Selected and Invited Papers Buy Physical Book Pattern Mining classification clustering constraint-based mining data management data mining database inductive databases knowledge discovery learning machine learning.   This book constitutes the thoroughly refereed joint postproceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases, KDID , held in Pisa, Italy in September in association with ECML/PKDD. Inductive Databases support data mining and the knowledge discovery process in a natural : Arno Siebes.

From the Publisher: Knowledge Discovery in Databases brings together current research on the exciting problem of discovering useful and interesting knowledge in spans many different approaches to discovery, including inductive learning, bayesian statistics, semantic query optimization, knowledge acquisition for expert systems, information theory, and fuzzy 1 sets. Introduction to Knowledge Discovery in Databases 3 Taxonomy is appropriate for the Data Mining methods and is presented in the next section. Figure The Process of Knowledge Discovery in Databases. The process starts with determining the KDD goals, and “ends” with the implementation of the discovered knowledge. Then the loop is closed - theFile Size: KB. This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID , held in association with ECML/PKDD. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and. The term knowledge discovery in databases or KDD, for short, was coined in to refer to the broad process of finding knowledge in data, and to emphasize the “high-level” application of particular data mining (DM) methods. The DM phase concerns, mainly, the means by which the patterns are extract Cited by: 3.

The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by Author: Rosa Meo. Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common. Get this from a library! Knowledge discovery in inductive databases: 4th international workshop, KDID , Porto, Portugal, October 3, revised selected and invited papers. [Francesco Bonchi; Jean-François Boulicaut;]. Add tags for "Knowledge discovery in inductive databases: Third International Workshop, KDID , Pisa, Italy, Septem revised selected .