UTHM Institutional Repository

Scalable technique to discover items support from trie data structure

Noraziah, A. and Abdullah, Zailani and Herawan, Tutut and Mat Deris, Mustafa (2012) Scalable technique to discover items support from trie data structure. In: Proceedings of the Third international conference on Information Computing and Applications (ICICA'12), 14-16 September 2012, Chengde, China.

Full text not available from this repository.


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 (Paper)
Uncontrolled Keywords: fast technique; frequent pattern tree; trie data structure
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 11 Apr 2013 06:31
Last Modified: 11 Apr 2013 06:31
URI: http://eprints.uthm.edu.my/id/eprint/3576
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item