智能数据可视分析技术综述

如何从海量数据中快速有效地挖掘出有价值的信息以更好地指导决策, 是大数据分析的重要目标. 可视分析是一种重要的大数据分析方法, 它利用人类视觉感知特性, 使用可视化图表直观呈现复杂数据中蕴含的规律, 并支持以人为本的交互式数据分析. 然而, 可视分析仍然面临着许多挑战, 例如数据准备代价高、交互响应高延迟、可视分析高门槛和交互模式效率低. 为应对这些挑战, 研究者从数据管理、人工智能等视角出发, 提出一系列方法以优化可视分析系统的人机协作模式和提高系统的智能化程度. 系统性地梳理、分析和总结这些方法, 提出智能数据可视分析的基本概念和关键技术框架. 然后, 在该框架下, 综述和分析国内外面向可视分析的数据准备、智能数据可视化、高效可视分析和智能可视分析接口的研究进展. 最后, 展望智能数据可视分析的未来发展趋势.

Intelligent Data Visualization Analysis Techniques: A Survey

How to quickly and effectively mine valuable information from massive data to better guide decision-making is an important goal of big data analysis. Visual analysis is an important big data analysis method, and it takes advantage of the characteristics of human visual perception, utilizes visualization charts to present laws contained in complex data intuitively, and supports human-centered interactive data analysis. However, the visual analysis still faces several challenges, such as the high cost of data preparation, high latency of interaction response, high threshold for visual analysis, and low efficiency of interaction modes. To address the above challenges, researchers propose a series of methods to optimize the human-computer interaction mode of visual analysis systems and improve the intelligence of the system by leveraging data management and artificial intelligence techniques. This study systematically sorts out, analyzes, and summarizes these methods and puts forward the basic concept and key technical framework of intelligent data visualization analysis. Then, under the framework, the research progress of data preparation for visual analysis, intelligent data visualization, efficient visual analysis, and intelligent visual analysis interfaces both in China and abroad is reviewed and analyzed. Finally, this study looks forward to the future development trend of intelligent data visualization analysis.