A Framework of Multi-Agent Professional Search Engine Based on Rough Set and Data Mining

Author

Wu, Hongjiang ; Peng, Qinke ; Huang, Yongxuan

Author_Institution

Syst. Eng. Inst., Xi´´an Jiaotong Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

4326

Lastpage

4330

Abstract

To meet the requirement, analyzing and mining on Web content based on machine learning is a major tendency of the computer science. This paper proposes a framework of multi-agent professional search engine system based on rough set and data mining. We build a multi-agent system, analyze the Web content based on rough set and data mining and enhance the learning capability of the agent based on Bayesian method. By this means, we can optimize the search strategies and improve the intelligence of search engine. Lastly, the architecture and implementation of ASE is discussed, and the performance is tested

Keywords

Internet; data mining; learning (artificial intelligence); multi-agent systems; rough set theory; search engines; Bayesian method; Web content; data mining; machine learning; multiagent professional search engine; rough set theory; Bayesian methods; Computer science; Data engineering; Data mining; Electronic mail; Machine learning; Multiagent systems; Search engines; Systems engineering and theory; Testing; Agent; Data mining; Professional search engine; 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.2006.1713192

Filename

1713192