An efficient method for mining sequential patterns with indices

Abstract

In recent years, mining informative data and discovering hidden information have become increasingly in demand. One of the popular means to achieve this is sequential pattern mining, which is to find informative patterns stored in databases. Its applications cover different areas and many methods have been proposed. Recently, pseudo-IDLists were proposed to improve both runtime and memory usage in the mining process. However, the idea cannot be directly used for sequential pattern mining as it only works on clickstream patterns, a more distinct type of sequential pattern. We propose adaptations and changes to the original idea to introduce SUI (Sequential pattern mining Using Indices). Comparing SUI with two other state-of-the-art algorithms on six test databases, we show that SUI has effective and efficient performance and memory usage. © 2021 Elsevier B.V.