Incrementally updating association rules based on multiple previously mined results

Incrementally updating association rules based on two or more classes of frequent item sets may reduce the costs of scanning the original database remarkably. However, it was considered as a method of saving time with more storage spaces. It is put forward in this paper that all frequent item sets of several minimal supports can be stored in a table with a little additional storage, and a representation model is given. Based on this model, the paper systematically discusses the problem of incrementally updating based on discovered association rules of several minimal supports. Theoretical analysis shows that the approach makes full use of the previous results and reduces the complexity of incremental updating algorithms.