Algorithm of mining fuzzy association rules in network management

Author

Liu, Pei-qi ; Li, Zeng-Zhi ; Zhao, Yin-Liang

Author_Institution

Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., China

Volume

1

fYear

2003

fDate

2-5 Nov. 2003

Firstpage

123

Abstract

This paper discusses the current status of the research about mining association rules in a database, which points out the shortcoming of classical a priori´s algorithm, and presents some theorems of mining association rules based on reducing records in a larger database. It also applies the theory of fuzzy sets to processing fuzzy data of traps in a network management. According to those theorems and the theory of fuzzy sets, we have designed the AprioriFuzzy algorithm to mine fuzzy association rules in database. Through the performance of AprioriFuzzy algorithm is analyzed and evaluated in this paper, this algorithm can save mining time about 30% and can mine fuzzy association rules in fuzzy data effectively. It has been implemented on PC in Visual C++6.0 and has been applied to mine the trap´s information in the network management based on SNMP protocol.

Keywords

data mining; database management systems; fuzzy set theory; protocols; visual languages; AprioriFuzzy algorithm; SNMP protocol; Visual C++6.0; a priori algorithm; fuzzy association rules mining; fuzzy set theory; network management; transactional database; Algorithm design and analysis; Association rules; Data engineering; Data mining; Engineering management; Fuzzy set theory; Fuzzy sets; Intelligent networks; Transaction databases; Visual databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2003 International Conference on

Print_ISBN

0-7803-8131-9

Type

conf

DOI

10.1109/ICMLC.2003.1264455

Filename

1264455