Visualization for frequent pattern mining
Date
2020-08-26
Authors
Hoi, Calvin Soen Him
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Abstract
In this fast information-technological world, data grow bigger and bigger. Big data refer to the huge volume, high velocity, wide variety and different veracity of the data flow. One of the big challenges is to aggregate and visualize the data mining results to the end user. To achieve a certain level of data validity for better data aggregation in estimation and prediction, the synergy of data visualization models and data mining strategies are necessary. In this MSc thesis, the focus is on frequent pattern visualization. This aims to visualize textual frequent patterns, which result in graphical representation with three important information: frequency distribution, cardinality distribution and superset-subset relationship. The designed and implemented visualization system for frequent pattern mining reveals interesting information and useful knowledge mined from the transactional databases for various applications and services.
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Keywords
Data mining, Data visualization, Visual analytics, Data science, Frequent patterns, Association rules, COVID-19