Title :
A novel mining Method of Global Negative Association Rules in Multi-Database
Author :
Li, Hong ; Shen, Yijun ; Hu, Xuegang
Author_Institution :
Dept. of Comput. Sci. & Technol., Hefei Univ., Hefei, China
Abstract :
Mining negative association rules in multi-database has attracted more and more attention. Most existing research focuses on unifying all negative rules discovered from different single databases into a single view. This paper presents a novel method for mining global negative association rules in multi-database. This method produces some infrequent itemsets of potential interest by scanning constructed multi-database frequent pattern tree, and extracts negative association rules of interest according to the proposed correlation model from multi-database. Experimental results show the effectiveness and efficiency of the proposed algorithm.
Keywords :
data mining; database management systems; correlation model; global negative association rule mining; itemsets; multidatabase frequent pattern tree; Application software; Association rules; Computer science; Data mining; Information processing; Intelligent networks; Itemsets; Laboratories; Tires; Transaction databases; association rules; global negative associations; multi-database mining;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357816
