A Multi-Agent Method for Parallel Mining Based on Rough sets

Author

Geng, Zhiqiang ; Zhu, Qunxiong

Author_Institution

Sch. of Inf. Sci. & Technol., Beijing Univ. of Chem. Technol.

Volume

2

fYear

0

fDate

0-0 0

Firstpage

5977

Lastpage

5980

Abstract

Rough set is a relatively new AI technique in data mining. Multi-agent system (MAS) has become a hotspot in the field of distributed AI recently. The challenge of the information age yet has not been resolved and the decision can´t be made precisely and in time according to market and requirements. To improve the performing efficiency of data mining system, the paper defines the novel operations and reasoning of agents and a multi-agent method for parallel rule mining based on rough sets is proposed. The information system is decomposed into many sub-information systems and every sub-information system can be an agent using rough set to acquire rules. From results of parallel mining, decisions can be made quickly and precisely

Keywords

data mining; inference mechanisms; multi-agent systems; rough set theory; agent reasoning; data mining; multiagent system; parallel rule mining; rough sets; subinformation system; Artificial intelligence; Chemical technology; Data mining; Educational technology; Information science; Intelligent agent; Probability; Rough sets; Set theory; Telecommunication computing; Data mining; Multi-agent; Parallel mining; Rough set;

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.2006.1714226

Filename

1714226