• DocumentCode
    3024341
  • Title

    Information highlighting

  • Author

    Ostler, Timothy

  • fYear
    1999
  • fDate
    1999
  • Firstpage
    528
  • Lastpage
    534
  • Abstract
    The paper reports on an empirical study in which, for the purposes of developing an automatic highlighting tool, 11 subjects were asked to highlight important passages in an 1111-word text. These results were cross-referenced with a range of word attributes in order to test hypotheses about the principles underlying highlighting decisions. With this data, a combination of selection criteria was proposed that was able to predict the probability of highlighting with a correlation of approximately 0.56, compared with an average correlation of 0.47 amongst the test subjects, and a figure of 0.30 for Word97´s highlighting feature. The paper argues that the common factor behind the most successful hypotheses was that they are all signals denoting “new” as opposed to “given” information at the discourse level. Although based on a very limited sample, this observation seems clear enough to make detecting such signals a promising candidate for further research
  • Keywords
    data visualisation; linguistics; text analysis; 1111-word text; Word97; automatic highlighting tool; election criteria; highlighting decisions; highlighting feature; information highlighting; word attributes; Bars; Electrical capacitance tomography; Encoding; Fluorescence; Humans; Ink; Materials testing; Signal detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Visualization, 1999. Proceedings. 1999 IEEE International Conference on
  • Conference_Location
    London
  • ISSN
    1093-9547
  • Print_ISBN
    0-7695-0210-5
  • Type

    conf

  • DOI
    10.1109/IV.1999.781608
  • Filename
    781608