Transferring information across language understanding model domains
First Claim
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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Accused Products
Abstract
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.
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Citations
21 Claims
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
- NLU”
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9. One or more computer-storage media having computer-executable instructions embodied thereon that when executed by a computing device perform the 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. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
- NLU”
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17. 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 training data to recognize an intent and a plurality of domain-specific entities, wherein the recognized intent and the plurality of domain-specific entities are associated with a slot of the domain-specific NLU; generating a plurality of candidate graph types for the slot of the domain-specific NLU by extracting, from a knowledge graph, a plurality of candidate graph types associated with each of the plurality of domain-specific entities, the candidate graph types comprising at least one compatible entity that is eligible for pairing with the recognized intent of the domain-specific NLU; assigning at least one of the plurality of candidate graph types as an individual graph type that the domain-specific NLU can accept based on a correlation score for each of the plurality of candidate graph types associated with the domain-specific entity, the individual graph type having the highest correlation score; expanding slot coverage of the domain-specific NLU by validating the pairing of the at least one compatible entity associated with the assigned 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. - View Dependent Claims (18, 19, 20, 21)
- NLU”
Specification