One Database Pass Algorithms of Mining Top-k Frequent Closed Itemsets

被引：0

作者：

Qiu, Yong ^{[1
]}

Lan, Yong-Jie ^{[1
]}

机构：

[1] Shandong Inst Business & Technol, Sch Comp Sience & Technol, Yantai 264005, Peoples R China

来源：

ICCSSE 2009: PROCEEDINGS OF 2009 4TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION | 2009年

关键词：

Data mining; Frequent Closed Itemsets; Top-k;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The FP-growth algorithm is a powerful algorithm to mine frequent patterns and it is non-candidate generation algorithm using a special structure FP-tree. Many algorithms proposed recently are based on FP-tree. These algorithms include all frequent itemsets mining, closed frequent itemsets mining and top-k closed frequent itemsets mining. However, it still requires two database scans, Although it is not a problem for static database, it is not efficient for frequent pattern mining, interactive and incremental mining. In order to enhance the efficiency of FP-tree based algorithms, propose a novel algorithm called QFPC which can create FP-tree with one database pass. Also propose a novel algorithm PFPTC to create FP-tree parallelly.

引用

页码：828 / 833

页数：6