Title :
Mining association rules with composite items
Author :
Ye, Xinfeng ; Keane, John A.
Author_Institution :
Dept. of Comput. Sci., Auckland Univ., New Zealand
Abstract :
Association rules can be used to express relationships between items of data. The process of mining associations rules is to analysis the data in a database to discover “interesting” rules. Existing algorithms for mining association rules require that a record in the database contain all the data items in a rule. This requirement makes it difficult to discover certain useful rules in some applications. To solve the problem, this paper describes an algorithm for mining association rules with composite items. The algorithm has the potential to discover rules which cannot be discovered by existing algorithms
Keywords :
database management systems; database theory; query processing; set theory; association rule mining; composite items; database mining; rule discovering; set theory; taxonomy; Association rules; Computer science; Data analysis; Data mining; Diseases; Itemsets; Lungs; Marine vehicles; Pain; Transaction databases;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.638164
