文本可视化研究综述被引量：53

A Survey of Text Visualization

下载PDF

导出

摘要随着海量文本的涌现,信息超载和数据过剩等问题促使了文本可视化技术的出现.文本可视化技术综合了文本分析、数据挖掘、数据可视化、计算机图形学、人机交互、认知科学等学科的理论和方法,为人们提供了一种理解复杂文本的内容、结构和内在规律等信息的有效手段.文中首先阐述了文本可视化的概念和重要性,然后按照不同可视化对象类型综述了文本可视化的研究现状,并介绍了典型的文本可视化方法与方案;最后,对文本可视化的未来研究方向进行了展望. With the emergence of massive texts, information overload and data redundancy raise great challenges for information processing. To address these issues, text visualization has been proposed for understanding the content, structure and patterns hidden behind complicated textual information. Text visualization integrates several techniques including text analysis, data mining, data visualization, computer graphics, human computer interaction, cognitive science and so on. In this paper, we first introduce the concepts of text visualization. Afterwards, we present the research achievements according to different visualization objects, and introduce typical visualization methods and schemes. As a conclusion, we give an outlook to future research directions of text visualization.

作者唐家渝刘知远孙茂松

机构地区智能技术与系统国家重点实验室

出处《计算机辅助设计与图形学学报》 EI CSCD 北大核心 2013年第3期273-285,共13页 Journal of Computer-Aided Design & Computer Graphics

基金国家自然科学基金重点项目(61133012)

关键词信息可视化可视分析文本分析信息抽取人机交互界面 information visualization, visual analytics, text analysis, information extraction, human-computer interaction interface

分类号 TP391 [自动化与计算机技术—计算机应用技术]

引文网络
相关文献

参考文献88

1Salton G, Wong A, Yang C S. A vector space model for automatic indexing [J]. Communications of the ACM, 1975, 18(11) : 613-620.
2Haroz S, Whitney D. How capacity limits of attention influence information visualization effectiveness [J]. IEEE Transactions on Visualization and Computer Graphics, 2012, 18(12) : 2402-2410.
3Heer J, Robertson G G. Animated transitions in statistical data graphics [J]. IEEE Transactions on Visualization and Computer Graphics, 2007, 13(6): 1240-1247.
4Lamping J, Rao R, Pirolli P. A focus+ context technique based on hyperbolic geometry for visualizing large hierarchies [C]//Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems. New York: ACM Press, 1995:401-408.
5Sebastiani F. Machine learning in automated text categorization [J]. ACM Computing Surveys, 2002, 34, (1) : 1-47.
6Viegas F B, Wattenberg M. TIMELINES: tag clouds and the case for vernacular visualization [J]. Interactions, 2008, 15 (4) : 49-52.
7Viegas F B, Wattenberg visualization with wordle Visualization and Computer M, Feinberg J. Participatory [J]. IEEE Transactions on Graphics, 2009, 15(6): 1137-1144.
8Koh K, Lee B, Kim B, etal. ManiWordle: providing flexible control over Wordle [J]. IEEE Transactions on Visualization and Computer Graphics, 2010, 16(6) : 1190-1197.
9Strobelt H, Oelke D, Rohrdantz C, etal. Document cards: a top trumps visualization for documents [J]. IEEE Transactions on Visualization and Computer Graphics, 2009, 15(6) : 1145-1152.
10Hearst M A. TileBars: visualization of term distribution information in full text information access [C] //Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems. New York: ACM Press, 1995:59-66.