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Deductive Data Mining using Granular Computing

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Encyclopedia of Database Systems

Synonyms

Deductive data mining, model for automated data mining; Rough set theory, granular computing on partition

Definition

What is Deductive Data Mining (DDM)? It is a methodology that derives patterns from the mathematical structure of a given stored data. Among three core techniques of data mining [1], classifications and association rule mining are deductive data mining, while clustering is not, because its algorithms often use some properties of the ambient space.

What is Granular Computing (GrC)? In general, it is a problem solving methodology deeply rooted in human thinking. For example, human body is granulated into head, neck, and etc. However, the main concerns here are on the data mining aspect of GrC. Two views are presented. One is based on current technology, and the other is on the incremental approach to the ultimate goal.

A) Mining Relational Databases (RDB) using GrC: In GrC, a relation K(also known as information table in rough set theory) is a knowledge...

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Author information

Authors and Affiliations

  1. San Jose State University, San Jose, CA, USA

    Tsau Young (T. Y.) Lin

Authors
  1. Tsau Young (T. Y.) Lin
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Editor information

Editors and Affiliations

  1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU (Professor) (Professor)

  2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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© 2009 Springer Science+Business Media, LLC

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Lin, T.Y.(. (2009). Deductive Data Mining using Granular Computing. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_767

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