Data, Information and Knowledge Visualization for Frequent Patterns

被引:3
|
作者
Hoi, Calvin S. H. [1 ]
Leung, Carson K. [1 ]
Pazdor, Adam G. M. [1 ]
机构
[1] Univ Manitoba, Dept Comp Sci, Winnipeg, MB, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
data visualization; information visualization; knowledge visualization; pattern visualization; visual analytics; frequent pattern; frequent itemset; trustworthy artificial intelligence; ASSOCIATION RULES;
D O I
10.1109/IV56949.2022.00045
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the current fast information-technological world, data are kept growing bigger. Big data refer to the data flow of huge volume, high velocity, wide variety, and different levels of veracity. Embedded in these big data are implicit, previously unknown, but valuable information and knowledge. With huge volumes of information and knowledge that can be discovered by techniques like data mining, a challenge is to validate and visualize the data mining results. To validate data for better data aggregation in estimation and prediction and for establishing trustworthy artificial intelligence, the synergy of visualization models and data mining strategies are needed. Hence, in this paper, we present a solution for data, information and knowledge visualization for frequently occurring patterns. Our solution transforms textual frequent patterns into their equivalent but more comprehendible graphical representations with important information: frequency distribution. The solution reveals interesting information and valuable knowledge mined from the transactional databases in various applications and services. Evaluation with real-life data demonstrates the effectiveness and practicality of our solution in visualizing data and information of the discovered frequent patterns.
引用
收藏
页码:221 / 226
页数:6
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