文章基本信息

标题：An Improvised Frequent Pattern Tree Based Association Rule Mining Technique with Mining Frequent Item Sets Algorithm and a Modified Header Table
本地全文：下载
作者：Vandit Agarwal ; Mandhani Kushal ; Preetham Kumar 等
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2015
卷号：5
期号：2
页码：39
DOI：10.5121/ijdkp.2015.5204
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：In today’s world there is a wide availability of huge amount of data and thus there is a need for turning thisdata into useful information which is referred to as knowledge. This demand for knowledge discoveryprocess has led to the development of many algorithms used to determine the association rules. One of themajor problems faced by these algorithms is generation of candidate sets. The FP-Tree algorithm is one ofthe most preferred algorithms for association rule mining because it gives association rules withoutgenerating candidate sets. But in the process of doing so, it generates many CP-trees which decreases itsefficiency. In this research paper, an improvised FP-tree algorithm with a modified header table, alongwith a spare table and the MFI algorithm for association rule mining is proposed. This algorithm generatesfrequent item sets without using candidate sets and CP-trees.
关键词：Association rules; FP-tree; Modified header table; Frequent Item Set; Frequent Pattern Tree