WLAR-Viz: Weighted least association rules visualization

Noraziah, Ahmad and Zailani, Abdullah and Herawan, Tutut and Mustafa, Mat Deris (2012) WLAR-Viz: Weighted least association rules visualization. In: 3rd International Conference on Information Computing and Applications (ICICA 2012), 14-16 September 2012 , Chengde, China. pp. 592-599.. ISBN 978-3-642-34062-8

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Abstract

Mining weighted least association rules has been an increasing demand in data mining research. However, mining these types of rules often facing with difficulties especially in identifying which rules are really interesting. One of the alternative solutions is by applying the visualization model in those particular rules. In this paper, a model for visualizing weighted least association rules is proposed. The proposed model contains five main steps, including scanning dataset, constructing Least Pattern Tree (LP-Tree), applying Weighted Support Association Rules (WSAR*), capturing Weighted Least Association Rules (WELAR) and finally visualizing the respective rules. The results show that by using a three dimensional plots provide user friendly navigation to understand the weighted support and weighted least association rules.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Weighted least association rules; Data mining; Visualization
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 03:20
Last Modified: 23 Mar 2020 03:20
URI: http://umpir.ump.edu.my/id/eprint/27027
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