An Efficient Approach to Discovering Sequential Patterns in Large Databases

Mining sequential patterns is to discover sequential purchasing behaviors of most customers from a large amount of customer transactions. The previous approaches for mining sequential patterns need to repeatedly scan the large database, and take a large amount of computation time to find frequent sequences, which are very time consuming. In this paper, we present an algorithm SSLP to find sequential patterns, which can significantly reduce the number of the database scans. The experimental results show that our algorithms are more efficient than the other algorithms.