Title :
An efficient projected database method for mining sequential association rules
Author :
Chen, Yi-Chun ; Lee, Guanling
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Dong Hwa Univ., Hualien, Taiwan
Abstract :
The mining of sequential patterns has been studied for several years, however, to our best knowledge, no study has considered the mining of sequential association rules despite such rules also providing valuable knowledge about many real applications. The sequential association rule represent that a set of items usually occur after a specific order sequence. In this paper, the concept of sequential association rule is proposed and an efficient algorithm, the SAR (Sequential Association Rules) algorithm, is proposed to discover these hidden knowledge. A set of experiments is also performed to show that the benefit of our approach.
Keywords :
data mining; SAR algorithm; projected database method; sequential association rules mining; sequential pattern mining; Algorithm design and analysis; Association rules; Itemsets; Obesity; data mining; projected database method; sequential association rule;
Conference_Titel :
Digital Information Management (ICDIM), 2010 Fifth International Conference on
Conference_Location :
Thunder Bay, ON
Print_ISBN :
978-1-4244-7572-8
DOI :
10.1109/ICDIM.2010.5664724