Visual Exploration based Approach for Extracting the Interesting Association Rules (유용한 연관 규칙 추출을 위한 시각적 탐색 기반 접근법)

Kim, Jun-Woo (김준우); Kang, Hyun-Kyung (강현경)

Visual Exploration based Approach for Extracting the Interesting Association Rules

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2013, 18(9), pp.177~187
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

Kim, Jun-Woo ¹, Kang, Hyun-Kyung ²

¹동아대학교
²신라대학교

Accredited

ABSTRACT

Association rule mining is a popular data mining technique with a wide range of application domains, and aims to extract the cause-and-effect relations between the discrete items included in transaction data. However, analysts sometimes have trouble in interpreting and using the plethora of association rules extracted from a large amount of data. To address this problem, this paper aims to propose a novel approach called HTM for extracting the interesting association rules from given transaction data. The HTM approach consists of three main steps, hierarchical clustering,table-view, and mosaic plot, and each step provides the analysts with appropriate visual representation. For illustration, we applied our approach for analyzing the mass health examination data, and the result of this experiment reveals that the HTM approach help the analysts to find the interesting association rules in more effective way.

KEYWORDS

Association rule mining, Transaction data, Pre-processing, Visualization, Hierarchical clustering

Citation status

* References for papers published after 2024 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

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Journal of The Korea Society of Computer and Information 2024 KCI Impact Factor : 0.81