Title :
A Novel Algorithm for Dynamic Mining of Association Rules
Author :
Jian, Wu ; Ming, Li Xing
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
Abstract :
Nowadays, communication network turns to be more complex, once there occurs a failure, there will result in multi-alarm-events which require relevant transactions. This paper describes the alarm correlation in communication networks based on data mining. The association rules from self-adaptation for dynamic network resource and service that build new rule by fully utilizing and maintaining rules formed before while transactions grow/delete or minimum support changes which enables the framework is easily updated and new discovery methods be readily incorporated within it. Both theoretical analysis and computer simulations illustrate outstanding performance of the proposed models, which can be further optimized by experiments for specific environment.
Keywords :
data mining; database management systems; alarm correlation; communication network; dynamic association rule mining; dynamic network resource; failure; multialarm events; self adaptation; Association rules; Communication networks; Data engineering; Data mining; Frequency; Heuristic algorithms; Itemsets; Knowledge engineering; Performance analysis; Transaction databases;
Conference_Titel :
Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on
Conference_Location :
Adelaide, SA
Print_ISBN :
978-0-7695-3090-1
DOI :
10.1109/WKDD.2008.32