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Hybrid learning system for natural language understanding

  • US 10,497,366 B2
  • Filed: 01/02/2019
  • Issued: 12/03/2019
  • Est. Priority Date: 03/23/2018
  • Status: Active Grant
First Claim
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1. An agent automation system, comprising:

  • a memory configured to store an intent/entity model and a natural language understanding (NLU) framework, wherein the intent/entity model associates defined intents with sample utterances, and wherein the sample utterances encode defined entities as parameters of the defined intents within the intent/entity model; and

    a processor configured to execute instructions of the NLU framework to cause the agent automation system to perform actions comprising;

    generating a meaning representation from an annotated utterance tree of an utterance by combining a plurality of vectors of the annotated utterance tree using stored coefficients to calculate a respective subtree vector for each intent subtree of the annotated utterance tree, wherein each of the plurality of vectors is associated with a particular node or subtree that depends from each intent subtree, wherein the stored coefficients provide focus, attention, and magnification (FAM) to the calculation of each respective subtree vector, and wherein the meaning representation has a tree structure that indicates a syntactic structure of the utterance and has one or more subtree vectors indicating a semantic meaning of one or more intent subtrees of the meaning representation;

    searching the meaning representation of the utterance against an understanding model to extract intents and entities of the utterance based on the one or more subtree vectors of the meaning representation, wherein the understanding model comprises a plurality of meaning representations derived from the sample utterances of the intent/entity model; and

    providing the intents and entities of the utterance to a behavior engine (BE) of the agent automation system, wherein the BE is configured to perform one or more actions in response to the intents and entities of the utterance.

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