期刊文献+

大数据可视分析综述 被引量:418

Visual Analytics Towards Big Data
下载PDF
导出
摘要 可视分析是大数据分析的重要方法.大数据可视分析旨在利用计算机自动化分析能力的同时,充分挖掘人对于可视化信息的认知能力优势,将人、机的各自强项进行有机融合,借助人机交互式分析方法和交互技术,辅助人们更为直观和高效地洞悉大数据背后的信息、知识与智慧.主要从可视分析领域所强调的认知、可视化、人机交互的综合视角出发,分析了支持大数据可视分析的基础理论,包括支持分析过程的认知理论、信息可视化理论、人机交互与用户界面理论.在此基础上,讨论了面向大数据主流应用的信息可视化技术——面向文本、网络(图)、时空、多维的可视化技术.同时探讨了支持可视分析的人机交互技术,包括支持可视分析过程的界面隐喻与交互组件、多尺度/多焦点/多侧面交互技术、面向Post-WIMP的自然交互技术.最后,指出了大数据可视分析领域面临的瓶颈问题与技术挑战. Visual analytics is an important method used in big data analysis. The aim of big data visual analytics is to take advantage of human’s cognitive abilities in visualizing information while utilizing computer’s capability in automatic analysis. By combining the advantages of both human and computers, along with interactive analysis methods and interaction techniques, big data visual analytics can help people to understand the information, knowledge and wisdom behind big data directly and effectively. This article emphasizes on the cognition, visualization and human computer interaction. It first analyzes the basic theories, including cognition theory, information theory, interaction theory and user interface theory. Based on the analysis, the paper discusses the information visualization techniques used in mainstream applications of big data, such as text visualization techniques, network visualization techniques, spatio-temporal visualization techniques and multi-dimensional visualization techniques. In addition, it reviews the interaction techniques supporting visual analytics, including interface metaphors and interaction components, multi-scale/multi-focus/multi-facet interaction techniques, and natural interaction techniques faced on Post-WIMP. Finally, it discusses the bottleneck problems and technical challenges of big data visual analytics.
出处 《软件学报》 EI CSCD 北大核心 2014年第9期1909-1936,共28页 Journal of Software
基金 国家自然科学基金(61103096) 国家高技术研究发展计划(863)(2013AA041302) 国家重点基础研究发展计划(973)(2014CB340300) 中央高校基本科研业务基金
关键词 大数据 可视化 信息可视化 可视分析 人机交互 云计算 big data visualization information visualization visual analytics human-computer interaction cloud computing
  • 相关文献

参考文献10

二级参考文献149

  • 1Johnson B, Shneiderman B. Tree-Maps: A space-filling approach to the visualization of hierarchical information. In: Nielson GM, Rosenblum L, eds. Proc. of the 2nd IEEE Visualization Conf. Los Alamitos: IEEE Computer Society Press, 1991. 284-291.
  • 2Van HF, Van WJ. Beamtrees: Compact visualization of large hierarchies. In: Wong PC, Andrews K, eds. Proc. of the IEEE Symp. on Information Visualization. Los Alamitos: IEEE Computer Society Press, 2002.31-39.
  • 3Van WJ, Van WH. Cushion Treemaps: Visualization of Hierarchical Information. In: Bryson S, Rhyne TM, eds. Proc. of the IEEE Symp. on Information Visualization. Los Alamitos: IEEE Computer Society Press, 1999.73-78.
  • 4Bederson BB, Shneiderman B. Ordered and quantum treemaps: Making effective use of 2D space to display hierarchies. ACM Trans. on Graphics, 2002,21(4):833-854.
  • 5Itoh T, Yamaguchi Y, Ikehata Y, Kajinaga Y. Hierarchical data visualization using a fast rectangle-packing algorithm. IEEE Trans. on Visualization and Computer Graphics, 2004,10(3):302-313.
  • 6Balzer M, Deussen O. Voronoi Treemaps for the visualization of software metrics. In: Naps T, Pauw WD, eds. Proc. of the 2005 ACM Symp. on Software visualization. New York: ACM Press, 2005. 165-172.
  • 7Chi EH, Pitkow J, Mackinlay J, Pirolli P, Gossweiler R, Card SK. Visualizing the evolution of Web ecologies. In: Karat CM, Lund A, Coutaz J, Karat J, eds. Proc. of the SIGCHI Conf. on Human Factors in Computing Systems. New York: ACM Press, 1998. 400-407.
  • 8Stasko J, Zhang E. Focus+Context display and navigation techniques for enhancing radial, space-filling hierarchy visualization. In: Mackinlay J, Roth S, Keim DA, eds. Proc. of the IEEE Symp. on Information Visualization. Los Alamitos: IEEE Computer Society Press, 2000. 57-65.
  • 9Feng YD. Research on key issues for information visualization [Ph.D. Thesis]. Beijing: Peking University, 2001 (in Chinese with English abstract).
  • 10Fumas GW. Generalized fisheye views. In: Mantei M, Orbeton P, eds. Proc. of the SIGCHI Conf. on Human Factors in Computing Systems. New York: ACM Press, 1986. 16-23.

共引文献569

同被引文献3458

引证文献418

二级引证文献2848

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部