Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Deductive Data Mining Using Granular Computing

  • Tsau Young Lin
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_767

Synonyms

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

Definition of the Subject

What is deductive data mining (DDM)? It is a methodology that mathematically deduces patterns from the structure of the stored data. Among the three core techniques of data mining [1], classifications and association rule mining are deductive data mining. For clustering, its algorithms often use some properties of the ambient space, so we shall not include them. For this entry, we will focus on illustrating the idea on associations (association rules without “if-then”). Technically, we refer an association by the term a frequent itemset.

In relational database (RDB), a relation is a (time-varying) knowledge representation of a (time-varying) universe U of discourse (a set of entities) in terms of a (time-varying) set of attributes \({\mathcal {A}}=\{A_{1}, A_{2}, \ldots A_{n} \}\)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceSan Jose State UniversitySan JoseUSA