Study on Tourism Emergency Attribute Reduction Based on Rough Set

Author

Gao Tian ; Du Junping ; Wang Su

Author_Institution

Beijing Key Lab. of Intell. Telecommun. Software & Multimedia, Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

This paper describes attribute extraction, attribute classification and data cleaning process in tourism emergency, builds a widely applicable decision table, and uses the attribute reduction algorithm based on the importance of Pawlak property. The results proves that the decision table after reduction is more beneficial to obtain useful decision rules, on the premise of maintaining constant dependence of condition attributes and decision attributes.

Keywords

decision tables; rough set theory; travel industry; Pawlak property; attribute classification; attribute extraction; condition attributes; constant dependence; data cleaning process; decision attributes; decision rules; decision table; rough set; tourism emergency attribute reduction; Cleaning; Computer science; Data analysis; Data mining; Economic forecasting; Industrial accidents; Industrial economics; Information analysis; Safety; Software algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5365575

Filename

5365575