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GENERATING NATURAL-LANGUAGE TEXT DESCRIPTIONS OF DATA VISUALIZATIONS

  • US 20200134074A1
  • Filed: 10/26/2018
  • Published: 04/30/2020
  • Est. Priority Date: 10/26/2018
  • Status: Abandoned Application
First Claim
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1. A method, comprising:

  • obtaining, with one or more processors, a set of candidate captions associated with one or more data visualizations, wherein;

    the set of candidate captions includes at least some natural language captions, andat least some of the one or more data visualizations are associated with a plurality of the candidate captions in the set;

    obtaining, with one or more processors, criteria designating whether the candidate captions are descriptive of potential instances of the one or more data visualizations, wherein the potential instances are producible by applying data to be visualized to the one or more data visualizations;

    generating, with one or more processors, data to be visualized;

    producing, with one or more processors, a plurality of simulated instances of each of the one or more data visualizations;

    determining, with one or more processors, which of the captions apply to each of the simulated instances of each of the one or more data visualizations based on whether the simulated instances satisfy corresponding criteria among the obtained criteria;

    causing, with one or more processors, captions determined to be applicable to be presented by one or more user computing devices in visual association with corresponding simulated instances of data visualizations to which captions are determined to apply;

    receiving, with one or more processors, feedback obtained via the one or more user computing devices indicative of whether presented captions are perceived as descriptive of the corresponding simulated instances of data visualizations;

    adjusting, with one or more processors, the criteria based on the feedback; and

    storing, with one or more processors, the adjusted criteria in memory.

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