A Method of Mining the Meta-association Rules for Dynamic Association Rule Based on the Model of AR-Markov

Author

Jingjing, Feng ; Qingfei, Zeng ; Zhonglin, Zhang

Author_Institution

Sch. of Electron. & Inf. Eng., Lanzhou Jiaotong Univ., Lanzhou, China

Volume

2

fYear

2010

fDate

24-25 April 2010

Firstpage

210

Lastpage

214

Abstract

Based on the dynamic association rules, this paper puts forward the formal definition of meta-rules which makes use of the support vector and confidence vector as evaluation of rules, and introduces the usual mining process of the Meta-association Rules for dynamic association rule by the model of AR-Markov, the examples show that this method is effective in the analysing and predicting the change tendency of Meta-association Rules´ support value and confidence value.

Keywords

Markov processes; data mining; meta data; support vector machines; AR-Markov; confidence vector; dynamic association rule; meta-association rules mining; support vector; Association rules; Computer networks; Data mining; Decision making; Information analysis; Information security; Predictive models; Technology forecasting; Transaction databases; Wireless communication; AR-Markov Model; dynamic association rule; forecast; meta-association rule;

fLanguage

English

Publisher

ieee

Conference_Titel

Networks Security Wireless Communications and Trusted Computing (NSWCTC), 2010 Second International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-0-7695-4011-5

Electronic_ISBN

978-1-4244-6598-9

Type

conf

DOI

10.1109/NSWCTC.2010.248

Filename

5480826