Top-N Frequent Itemsets Mining Algorithm Based on Greedy Method

Top-N frequent item sets mining gets the interesting results by appointing the quantity of the most frequent item sets. It is an important data mining application. This article proposed a Top-N frequent item sets mining algorithm based on greedy method. The obtained Top-N item sets are stored in a static doubly linked list. Join two frequent item sets which have the highest support in the not joined Top-N item sets. The frequent item sets have the higher support that can be generated early. We can adjust the border support quickly. According to the analysis and experiments, this new algorithm demonstrates better performance than Apriori and NApriori on the time and space performance.