Algorithm of Hierarchical Reduction Based on Rough Entropy

Author

Dong, Wei ; Wang, Jianhui ; Xu, Lin ; Gu, Shusheng

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang

Volume

1

fYear

0

fDate

0-0 0

Firstpage

4374

Lastpage

4377

Abstract

We propose a scheme based on rough entropy to cluster the concept hierarchy for resolving the problem of discovering knowledge from large databases. The paper defines rough entropy and establishes the relation between the information system knowledge and rough entropy. It offers a new algorithm based on rough entropy and attribute significance to construct information. The attributes are classified to different parts allocated at several layers, so the knowledge in the information system can be presented hierarchically with multiple granularities at multiple layers. The time complexity of the algorithm is analyzed and the algorithm is used to a control decision, which verifies the effectiveness

Keywords

computational complexity; data mining; entropy; information systems; rough set theory; very large databases; hierarchical reduction; information system; knowledge discovery; large databases; rough entropy; rough set; time complexity; Algorithm design and analysis; Clustering algorithms; Data engineering; Databases; Educational institutions; Entropy; High definition video; Information science; Information systems; Knowledge engineering; hierarchical reduction; rough entropy; rough set; time complexity;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713203

Filename

1713203