An Improved Incremental Queue Association Rules for Mining Mass Text

Association rules is an important data analysis and mining method, and the FP-Growth and the traditional FP-Tree algorithm is used in the full confidence of rules. This paper proposes a incremental queue algorithm models based on association rules, which is the improved FP4W-Growth algorithm. It is proposed and applied to the calculation the association text by the correlation of incremental queue. Its feasibility is validated by experiment. After optimization of the algorithm and model, it can find hidden and useful new information and new pattern. And those rules found in text can be potentially used as the scientific decision-making methods.