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Scalable mining of trending insights from text

  • US 10,733,221 B2
  • Filed: 03/30/2016
  • Issued: 08/04/2020
  • Est. Priority Date: 03/30/2016
  • Status: Active Grant
First Claim
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1. A method comprising:

  • storing, in an electronic data store, a plurality of digital documents;

    accessing the electronic data store to identify a first plurality of topics in the plurality of digital documents;

    determining a co-occurrence of each pair of topics in a plurality of pairs of topics in the first plurality of topics;

    based on a deduplication threshold and the co-occurrence of each pair of topics in the plurality of pairs of topics, identifying a strict subset of the plurality of pairs of topics;

    based on the strict subset of the plurality of pairs of topics, removing multiple topics from the first plurality of topics to identify a second plurality of topics that includes fewer topics than the first plurality of topics;

    for each topic in the second plurality of topics;

    determining one or more frequencies of said each topic, wherein determining the one or more frequencies comprises, for each time period of one or more time periods, determining a frequency of said each topic during said each time period;

    determining a particular frequency of said each topic in a particular time period that is subsequent to the one or more time periods;

    generating a trending score for said each topic based on the one or more frequencies and the particular frequency;

    generating a ranking of the second plurality of topics based on the trending score for each topic in the second plurality of topics;

    causing the second plurality of topics to be arranged on a screen of a computing device based on the ranking of the second plurality of topics;

    wherein the method is performed by one or more computing devices.

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