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Transferring information across language understanding model domains

  • US 10,191,999 B2
  • Filed: 04/30/2014
  • Issued: 01/29/2019
  • Est. Priority Date: 04/30/2014
  • Status: Active Grant
First Claim
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1. A computer-implemented method of expanding slot coverage for a domain-specific natural language understanding (“

  • NLU”

    ) system, the method comprising;

    accessing a plurality of queries from labeled training data for a classifier used to recognize an intent within the domain-specific NLU, wherein the intent is associated with a slot of the domain-specific NLU;

    identifying a plurality of entities that occur in the slot of the domain-specific NLU within the plurality of queries;

    extracting, from a knowledge graph, a graph type for each of the plurality of entities to generate a plurality of candidate graph types for the slot of the domain-specific NLU, the candidate graph types comprising at least one compatible entity that is eligible for pairing with the recognized intent of the domain-specific NLU;

    calculating a correlation score for each graph type in the plurality of candidate graph types for pairing the at least one compatible entity with the recognized intent of the domain-specific NLU;

    assigning an individual graph type having the highest correlation score as the graph type the domain-specific NLU slot can accept;

    expanding slot coverage for the domain-specific NLU by validating the pairing of the at least one compatible entity associated with the assigned individual graph type with the recognized intent of the domain-specific NLU; and

    utilizing the validated pairing of the compatible entity and the recognized intent to interpret a natural language input of a query.

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