UMP Institutional Repository

A Scalable Algorithm for Constructing Frequent Pattern Tree

Noraziah, Ahmad and Herawan, Tutut and Zailani, Abdullah and Mustafa, Mat Deris (2014) A Scalable Algorithm for Constructing Frequent Pattern Tree. International Journal of Intelligent Information Technologies (IJIIT), 10 (1). pp. 42-56. ISSN 1548-3657 (print); 1548-3665 (online)

[img] PDF
fskkp-2014-noraziah-Scalable_algorithm.pdf
Restricted to Repository staff only

Download (402kB) | Request a copy

Abstract

Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. In typical FP-Tree construction, besides the prior knowledge on support threshold, it also requires two database scans; first to build and sort the frequent patterns and second to build its prefix paths. Thus, twice database scanning is a key and major limitation in completing the construction of FP-Tree. Therefore, this paper suggests scalable Trie Transformation Technique Algorithm (T3A) to convert our predefined tree data structure, Disorder Support Trie Itemset (DOSTrieIT) into FP-Tree. Experiment results through two UCI benchmark datasets show that the proposed T3A generates FP-Tree up to 3 magnitudes faster than that the benchmarked FP-Growth.

Item Type: Article
Uncontrolled Keywords: Data Mining; Association Rules; Frequent patterns; Scalable Algorithm
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: PM Dr. Noraziah Ahmad
Date Deposited: 17 Sep 2014 02:55
Last Modified: 02 Feb 2018 03:05
URI: http://umpir.ump.edu.my/id/eprint/6623
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item