An incremental attribute reduction approach with concept lattice for ALDD

Hong Chun Yuan*, Yan Hua Wang, De Xing Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As an effective tool for knowledge discovery, concept lattice has been successfully applied to various fields. One of the key problems of knowledge discovery is knowledge reduction. The existing work on attribute reduction has not focused on aquatic lives disease diagnosis (ALDD). This paper describes an improved incremental approach of attribute reduction in concept lattice for ALDD. Firstly, the main definition of the concept lattice is introduced. Secondly, the attributes within the framework of equivalence classes are discussed. Finally, the incremental algorithm of attribute reduction in concept lattice for ALDD is presented. Based on the algorithm, we can easily diagnose the aquatic lives diseases. The examples results validate the effectiveness of approach.

Original languageEnglish
Title of host publication2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010
Pages607-610
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010 - Changsha, China
Duration: 11 May 201012 May 2010

Publication series

Name2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010
Volume1

Conference

Conference2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010
Country/TerritoryChina
CityChangsha
Period11/05/1012/05/10

Keywords

  • Attribute reduction
  • Concept lattice
  • Equivalence classes
  • KDD

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