Title :
Extended MRI-Cube Algorithm for Mining Multi-Relational Patterns
Author :
Liang, Bao ; Hong, Xiaoguang ; Zhang, Lei ; Li, Shuai
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ.
Abstract :
Association rule mining is one of the most important and basic technique in data mining, which has been studied extensively and has a wide range of applications. Two stream of previous work has dealt with the discovery of association rules over multiple relations: prolog databases and datalog queries. The MRI Iceberg-cubes mining method introduces a new perspective. However, it does not take the cyclic join paths into account, therefore, in this paper, we will introduce an algorithm, Extended-MRI-cube, which is based on the MRI-Cube algorithm, to handle the cyclic join path situation. Experiments show it is more applicable and effective than the previous one.
Keywords :
data mining; graph theory; query processing; relational databases; association rule mining; cyclic join path algorithm; data mining; datalog query; extended multi relational iceberg-cube algorithm; multi relational pattern mining; prolog database; Application software; Association rules; Computer science; Data analysis; Data mining; Database systems; Logic programming; Partitioning algorithms; Relational databases; Scalability; Data mining; association rules; bottom up computation; multi-relational patterns;
Conference_Titel :
Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3398-8
Electronic_ISBN :
978-0-7695-3398-8
DOI :
10.1109/ICYCS.2008.165