Incremental Updating Algorithm Based on Frequent Pattern Tree for Mining Association Rules
Yu Zhu · Chinese Journal of Computers · 2003
The discovery of interesting association rules among huge amounts of business transaction records can help in many business decision making processes, such as catalog design, cross marketing, and loss leader analysis. There have been many algorithms proposed for efficient discovery of association rules in large databases. However, a little work has been done on maintenance of discovered association rules. This paper presents an incremental updating algorithm based on FP tree for mining association rules in the cases including inserting the transactions in the databases and modifying support. The proposed algorithm makes use of the previous mining result to cut down the cost of finding new rules in an updated database. Comparing with FUP algorithm, the authors also offer some experiments to show that the new algorithm is more efficient.