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Granular Computing on Extensional Functional Dependencies for Information System

  • Qiusheng An
  • Junyi Shen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3066)

Abstract

In this paper, a new approach to discover extensional functional dependencies for information systems is presented based on information granules using their bit representations. The principle of information granules, granular computing and the machine oriented model for data mining are investigated firstly. In addition, the approach to identify the classical functional dependencies, identity dependencies and partial dependencies is discussed and some conclusions on extensional functional dependencies are obtained. The information granules are represented with bit, then the data format can be closed to the inner representations of the computer, hence, the patterns contained in the information system can be directly mined.

Keywords

Data Mining Functional Dependency Information Granule Granular Computing Attribute Subset 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Qiusheng An
    • 1
  • Junyi Shen
    • 2
  1. 1.Department of Mathematics and ComputerShanxi Normal UniversityLinfenChina
  2. 2.School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anChina

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