Efficiently Mining of Maximal Frequent Item Sets Based on FP-Tree

Abstract: During the process of mining maximal frequent item sets, when minimum support is little, superset checking is a kind of time-consuming and frequent operation in the mining algorithm. In this paper, a new algorithm FPMFI (frequent pattern tree for maximal frequent item sets) for mining maximal frequent item sets is proposed. It adopts a new superset checking method based on projection of the maximal frequent item sets, which efficiently reduces the cost of superset checking. In addition, FPMFI also compresses the conditional FP-Tree (frequent pattern tree) greatly by deleting the redundant information, which can reduce the cost of accessing the tree. It is proved by theoretical analysis that FPMFI has superiority and it is revealed by experimental comparison that the performance of FPMFI is superior to that of the similar algorithm based on FP-Tree more than one time. Key words: maximal frequent item set; frequent pattern tree; superset check; maximal frequent item sets projection 摘 要: 最大频繁项集的挖掘过程中,在最小支持度较小的情况下,超集检测是算法的主要耗时操作.提出了最大 频繁项集挖掘算 法 FPMFI(frequent pattern tree for maximal frequent item set)使用基于投影进行超集检测的机制,