Literature DB >> 18988967

The Word Tree, an interactive visual concordance.

Martin Wattenberg1, Fernanda B Viégas.   

Abstract

We introduce the Word Tree, a new visualization and information-retrieval technique aimed at text documents. A word tree is a graphical version of the traditional "keyword-in-context" method, and enables rapid querying and exploration of bodies of text. In this paper we describe the design of the technique, along with some of the technical issues that arise in its implementation. In addition, we discuss the results of several months of public deployment of word trees on Many Eyes, which provides a window onto the ways in which users obtain value from the visualization.

Entities:  

Year:  2008        PMID: 18988967     DOI: 10.1109/TVCG.2008.172

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  5 in total

1.  NLPReViz: an interactive tool for natural language processing on clinical text.

Authors:  Gaurav Trivedi; Phuong Pham; Wendy W Chapman; Rebecca Hwa; Janyce Wiebe; Harry Hochheiser
Journal:  J Am Med Inform Assoc       Date:  2018-01-01       Impact factor: 4.497

2.  Modeling Terminologies for Reusability in Faceted Systems.

Authors:  Daniel R Harris
Journal:  Proc IEEE Int Conf Inf Reuse Integr       Date:  2017-08-17

3.  Rapid and Reusable Text Visualization and Exploration Development with DELVE.

Authors:  Daniel R Harris; Ramakanth Kavuluru; Jerzy W Jaromczyk; Todd R Johnson
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2017-07-26

4.  Interactive Exploration of Longitudinal Cancer Patient Histories Extracted From Clinical Text.

Authors:  Zhou Yuan; Sean Finan; Jeremy Warner; Guergana Savova; Harry Hochheiser
Journal:  JCO Clin Cancer Inform       Date:  2020-05

5.  Analyzing the public discourse on works of fiction - Detection and visualization of emotion in online coverage about HBO's Game of Thrones.

Authors:  Arno Scharl; Alexander Hubmann-Haidvogel; Alistair Jones; Daniel Fischl; Ruslan Kamolov; Albert Weichselbraun; Walter Rafelsberger
Journal:  Inf Process Manag       Date:  2016-01       Impact factor: 6.222

  5 in total

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