Title :
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
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;
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
DOI :
10.1109/NSWCTC.2010.248
