Using Dynamic Data Mining in Association Rule Mining

The main objective of data mining is to rind interesting/useful knowledge for the user, as Rules are an important form of knowledge, some existing research has produced many algorithms for rule mining. These techniques, use the whole dataset to mine rules and then filter and/or rank the discovered rules in various ways to help the user identify useful ones., Data mining should provide tactical insights to Support the strategic directions, In this paper, we evaluate using a dynamic mining approach that uses knowledge discovered in previous episodes for classifying web documents. The proposed approach is shown to be effective for solving problems related to the efficiency of handling database updates, accuracy of data mining results, gaining more knowledge and interpretation of the results, and performance. Our results do not depend on the approach used to generate itemsets. in Our analysis, we have used an Apriori-like approach as a local procedure to generate large itemsets.