Mining Top-K Frequent Closed Patterns without Minimum Support

In this paper, we propose a new mining task: mining top-k frequent closed patterns of length no less than min , where k is the desired number of frequent closed patterns to be mined, and min is the minimal length of each pattern. An efficient algorithm, called TFP, is developed for mining such patterns without minimum support. Two methods, closed node count and descendant sum are proposed to effectively raise support threshold and prune FP-tree both during and after the construction of FP-tree. During the mining process, a novel top-down and bottom-up combined FP-tree mining strategy is developed to speed-up supportraising and closed frequent pattern discovering. In addition, a fast hash-based closed pattern verification scheme has been employed to check efficiently if a potential closed pattern is really closed. Our performance study shows that in most cases, TFP outperforms CLOSET and CHARM, two efficient frequent closed pattern mining algorithms, even when both are running with t...

• Type: Conference
• Year: 2002
• Where: ICDM
• Authors: Jiawei Han, Jianyong Wang, Ying Lu, Petre Tzvetkov
• Keywords: Data Mining, Frequent Closed Patterns, Frequent Pattern, ICDM 2002, Mining