A new algorithm is developed based on artificial immune system and on the improved model for association rules mining. The algorithm is both scalable and efficient in discovering significant relationships in weighted settings as illustrated by experiments performed on web usage datasets. We propose a strategy for maintaining association rules in dynamic databases. This method uses weighting technique to highlight new data. The experiments have shown that our approach is efficient and promising.
['Yidan Su', 'Xinyi Gu', 'Zhujuan Li']
Incremental updating Algorithm Based on Artificial Immune System For Mining Association Rules