An efficient projected database method for mining sequential association rules
Yi‐Chun Chen, Guanling Lee · 2010
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.