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Improving Performance in Big Data Visualization
Author: Tan Tam
Survey on Big Data Visualization Improving Performance of Big-Data visualization
Topic: Information Visualization amplifies cognition of human users to explore and discover data more efficiently and effectively. It has been applied in many areas from scientific research to business and education. Several methods and techniques have been utilized in this field in order to gain improved user performance and enhanced knowledge perception. The importance of information visualization has become more significant than ever as the amount of data being generated dramatically increased recently.
Problem: One of the key challenges of information visualization is performance. This is particularly important for big-data visualization. One possible approach for overcoming this challenge is sampling while maintaining fidelity of visualization aspects.
Method: In this paper, we conduct literature review on previous approaches of information visualization to identify factors affecting performance of big-data visualization. In particular, we review sampling approaches for improving performance of big-data visualization in order to identify gap in the literature, opportunities, and future research directions.
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