An Improved FP-Growth Algorithm Based on Compound Single Linked List

FP-growth algorithm is one of the most efficient approaches for frequent item set mining. In this article, an improved FP-growth algorithm based on Compound Single Linked List is proposed. There are two contributions in the new algorithm. One is to use the sequencing table and single linked list as the main data structure, the other is that it does not need to generate conditional FP-tree. An experiment is conducted to compare the efficiency between the original one and the improved one. It shows that the new one improves the algorithm both in runtime and the main memory consumption.