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). (Published)
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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 |
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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 |
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