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Visualizing Document Content

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Introduction to Text Visualization

Part of the book series: Atlantis Briefs in Artificial Intelligence ((ABAI,volume 1))

Abstract

Text is primarily made of words and always meant to contain content for information delivery. Content analysis is the earliest established method of text analysis (Holsti et al., The handbook of social psychology, vol 2, pp 596–692, 1968 [55]). Although studied extensively and systematically by linguists, related disciplines are roughly divided into two categories, structure and substance, according to their subjects of study (Ansari, Dimensions in discourse: elementary to essentials. Xlibris Corporation, Bloomington, 2013 [9]). Structure is about the surface characteristics that are visible for a valid text, such as word co-occurrence, text reuse, and grammar structure. On the other hand, substance is the umbrella term for all information that needs to be inferred from text, such as fingerprinting, topics, and events. Various techniques have been proposed to analyze these aspects. In this chapter, we will briefly review these techniques and the corresponding visualization systems.

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Notes

  1. 1.

    https://www.flickr.com/photos/tags.

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Authors and Affiliations

  1. IBM T. J. Watson Research Center, Yorktown Heights, New York, USA

    Nan Cao

  2. Microsoft Research Asia, Beijing, China

    Weiwei Cui

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  1. Nan Cao
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  2. Weiwei Cui
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Correspondence to Nan Cao .

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Cao, N., Cui, W. (2016). Visualizing Document Content. In: Introduction to Text Visualization. Atlantis Briefs in Artificial Intelligence, vol 1. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-186-4_5

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  • DOI: https://doi.org/10.2991/978-94-6239-186-4_5

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  • Online ISBN: 978-94-6239-186-4

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