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Optimized data visualization according to natural language query

  • US 10,572,473 B2
  • Filed: 10/09/2013
  • Issued: 02/25/2020
  • Est. Priority Date: 10/09/2013
  • Status: Active Grant
First Claim
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1. A method comprising:

  • accessing by a computer a corpus of numeric data;

    priming a synonym list with a plurality of absolute weights and a plurality of proportional weights, wherein each absolute weight is associated with a symbol and one of a plurality of numeric visualization formats, wherein each proportional weight is associated with a symbol and one of a plurality of numeric visualization formats, wherein values assigned to the proportional weights and to the absolute weights reflect greater suitability for a symbol to be visualized by a corresponding visualization format;

    receiving, from a user input device, by a computer, a query about a data corpus comprising a natural language expression;

    identifying, by a computer, using natural language processing, one or more symbols provided within the expression;

    removing, by a computer, one or more aliased meanings by translating uncontrolled language expressed by the one or more identified symbols within the expression to controlled language using one or more normalized symbols according to the primed synonym list;

    inferring, by a computer, using natural language processing of the translated controlled language, using one or more of a language dictionary, a model and an ontology, identified symbols, at least one characteristic, property or relationship within the data corpus about which the user is querying but which is not explicitly stated by the user in the expression;

    scoring, by a computer, each of the plurality of numeric data visualization formats according to the absolute weights and the proportional weights for each of the different numeric data visualization formats across all of the normalized symbols, wherein the different visualization formats comprise at least a plurality of different formats of charts selected from the group consisting of pie charts, bar graphs, stacked bar charts, time series plots, parts-of-the-whole illustrations, distribution charts, scattergrams, line charts, box plots, correlation charts, comparison charts, and heat maps; and

    generating, by a computer on a user interface device, a numeric data visualization of the corpus having a format according to the greatest scoring, wherein the format does not rely on any explicit user chart format or feature selections.

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