TRANSFERRING INFORMATION ACROSS LANGUAGE UNDERSTANDING MODEL DOMAINS

摘要

Aspects of the present invention provide a technique to validate the transfer of intents or entities between existing natural language model domains (hereafter “domain” or “NLU”) using click logs, a knowledge graph, or both. At least two different types of transfers are possible. Intents from a first domain may be transferred to a second domain. Alternatively or additionally, entities from the second domain may be transferred to an existing intent in the first domain. Either way, additional intent/entity pairs can be generated and validated. Before the new intent/entity pair is added to a domain, aspects of the present invention validate that the intent or entity is transferable between domains. Validation techniques that are consistent with aspects of the invention can use a knowledge graph, search query click logs, or both to validate a transfer of intents or entities from one domain to another.

主权项

1. A 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; identifying a plurality of entities that occur in the slot 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; calculating a correlation score for each graph type in the plurality of candidate graph types for the slot; and assigning an individual graph type having the highest correlation score for the slot as the graph type the slot can accept.