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Document visualization: an overview of current research

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As the number of sources and quantity of document information explodes, efficient and intuitive visualization tools are desperately needed to assist users in understanding the contents and features of a document, while discovering hidden information. This overview introduces fundamental concepts of and designs for document visualization, a number of representative methods in the field, and challenges as well as promising directions of future development. The focus is on explaining the rationale and characteristics of representative document visualization methods for each category. A discussion of the limitations of our classification and a comparison of reviewed methods are presented at the end. This overview also aims to point out theoretical and practical challenges in document visualization. WIREs Comput Stat 2014, 6:19–36. doi: 10.1002/wics.1285

Conflict of interest: The authors have declared no conflicts of interest for this article.

DocuBust of a science textbook rooted at {idea}. A search query for words starting with ‘pl’ has been performed. Nodes matching the query are highlighted in gold. (Reprinted with permission from Ref . Copyright 2009 The Eurographics Association and Blackwell Publishing Ltd)
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Alice's adventures in Wonderland in TextArc. http://www.textarc.arc.org/.
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Tag clouds.
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Multiple views of Jigsaw. (Reprinted with permission for Ref . Copyright 2008 Palgrave Macmillan)
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History flow shows the chocolate page on Wikipedia. The zigzag pattern which turns out that this is an argument over whether a certain type of surrealist sculpture exists or not. http://commons.wikimedia.org/wiki/File:English_Wikipedia_Treaty_of_Trianon_History_Flow.png.
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Explanation of the visualization design for history flow.
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The IEEE InfoVis 2008 proceeding corpus represented by Document Cards (DC). DC3 is switched to the page view on page2. In DC12 the term ‘tree diagram’ is clicked. The frequency of the term on each page is shown on the right side of the DC (the more red, the higher the frequency). (Reprinted with permission from Ref . Copyright 2009 IEEE)
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A portion of the ThemeRiver generated by the box office receipts from 1986 to 2007. http://infosthetics.com/archives/2008/02/ebb_flow_of_box_office_movies.html.
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IN‐SPIRE (a) ThemeView: mountain height represents a theme's strength. The distance between mountains represents their similarity. (b) Galaxy: a 2D view of clouds of document points. http://in‐spire.pnnl.gov/.
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A Document Arc Diagram generated from the text for the State of the Union Address for 2012. http://www.neoformix.com/Projects/DocumentArcDiagrams/index.html.
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WordTree shows all occurrences of ‘I have a dream’ in Martin Luther King's historical speech. http://www‐958.ibm.com/software/data/cognos/manyeyes/.
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The semantic graph obtained for a news article. http://saatviga.wordpress.com/2010/10/13/constructing‐semantic‐graphs‐from‐text‐documents/.
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Data Visualization > Computer Graphics
Data Mining > Text Mining

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