TOPSIS-based Recommender System for Big Data Visualizations

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Václav Stehlík
Mouzhi Ge


data visualization, Big Data, data visualization recommendation, TOPSIS


Big data analytics can enable effective data interpretation that leads to highquality decision making in organizations. Since the amount of data nowadays has significantly increased in various industries, it thus motivates the research of visualizations for interdisciplinary and collaborative domains. Although there is a large collection of visualization techniques, it is very time-consuming to choose proper visualization techniques for a specific dataset.
This paper therefore aims to analyze the typical and state-of-the-art data visualization techniques for big data. Differing from traditional visualizations such as line chart or bar chart, this paper focuses on reviewing a set of modern visualizations for big data in terms of analyzing their advantages and disadvantages. To facilitate choosing a proper visualization, a recommender model based on TOPSIS is further proposed. In order to validate the proposed model, a prototype of the big data visualization recommender system has been implemented to validate the applicability of the system.

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