Scalable technique to discover items support from trie data structure

Noraziah, Ahmad and Zailani, Abdullah and Herawan, Tutut and Mustafa, Mat Deris (2012) Scalable technique to discover items support from trie data structure. In: 3rd International Conference on Information Computing and Applications (ICICA 2012), 14-16 September 2012 , Chengde, China. pp. 500-507.. ISBN 978-3-642-34062-8

Scalable technique to discover items support from trie data structure.pdf

Download (273kB) | Preview


One of the popular and compact trie data structure to represent frequent patterns is via frequent pattern tree (FP-Tree). There are two scanning processes involved in the original database before the FP-Tree can be constructed. One of them is to determine the items support (items and their support) that fulfill minimum support threshold by scanning the entire database. However, if the changes are suddenly occurred in the database, this process must be repeated all over again. In this paper, we introduce a technique called Fast Determination of Item Support Technique (F-DIST) to capture the items support from our proposed Disorder Support Trie Itemset (DOSTrieIT) data structure. Experiments through three UCI benchmark datasets show that the computational time to capture the items support using F-DIST from DOSTrieIT is significantly outperformed the classical FP-Tree technique about 3 orders of magnitude, thus verify its scalability.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Frequent Pattern Tree; Trie Data Structure; Fast Technique
Subjects: Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 23 Mar 2020 03:40
Last Modified: 23 Mar 2020 03:40
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item