US 2022/0100972 A1Published application

Configurable generic language understanding models

AssigneeMicrosoft Technology Licensing, LLC

InventorsRuhi Sarikaya, Asli Celikyilmaz, Young-Bum Kim, Zhaleh Feizollahi, Nikhil Ramesh, Hisami Suzuki, Alexandre Rochette

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Abstract

Examples of the present disclosure describe systems and methods of configuring generic language understanding models. In aspects, one or more previously configured schemas for various applications may be identified and collected. A generic schema may be generated using the collected schemas. The collected schemas may be programmatically mapped to the generic schema. The generic schema may be used to train on ore more models. An interface may be provided to allow browsing the models. The interface may include a configuration mechanism that provides for selecting on or more of the models. The selected models may be bundled programmatically, such that the information and instructions needed to implement the models are configured programmatically. The bundled models may then be provided to a requestor.

Claims20

Dependent claims

A system comprising:

at least one processor;
and
memory coupled to the at least one processor, the memory comprising computer executable instructions that, when executed by the at least one processor, performs a method for configuring language understanding models, the method comprising:
receiving a request to create a generic schema;
collecting schema data associated with a first language understanding model and associated with a second language understanding model, wherein the schema data comprises a first set of domain data for a first domain identifier from a first domain and a second set of domain data from a second domain for a second domain identifier;
identifying a commonality of category between a first fine schema element in the first set of domain data and a second fine schema element in the second set of domain data;
mapping, in response to identifying the commonality, the first fine schema element and the second fine schema element to a third course schema element, wherein the third course schema element describes the identified commonality;
generating a generic schema using the collected schema data, wherein generating the generic schema comprises applying, to the generic schema, the mapping of the first fine schema element and the second fine schema element to the third course schema element;
using the generic schema data to train a plurality of language understanding models, wherein the training enables each of the plurality of language understanding models to process requests relating to the first domain and the second domain based on the mapping, wherein each of the plurality of language understanding models is trained using only a corresponding subset of course schema elements of the generic schema and fine schema elements from the first set of domain data and from the second set of domain data which were mapped to course schema elements in the corresponding subset of the generic schema, and wherein different language understanding models correspond to different subsets of course schema elements;
and
providing an interface to view the plurality of language understanding models with the first domain and second domain.

8 more elements

A method for configuring language understanding models, the method comprising:

receiving a request to create a generic schema;
collecting schema data associated with a first language understanding model and associated with a second language understanding model, wherein the schema data comprises a first set of domain data for a first domain identifier from a first domain and a second set of domain data from a second domain for a second domain identifier;
identifying a commonality of category between a first fine schema element in the first set of domain data and a second fine schema element in the second set of domain data;
mapping, in response to identifying the commonality, the first fine schema element and the second fine schema element to a third course schema element, wherein the third course schema element describes the identified commonality;
generating a generic schema using the collected schema data, wherein generating the generic schema comprises applying, to the generic schema, the mapping of the first fine schema element and the second fine schema element to the third course schema element;
using the generic schema data to train a plurality of language understanding models, wherein the training enables each of the plurality of language understanding models to process requests relating to the first domain and the second domain based on the mapping, wherein each of the plurality of language understanding models is trained using only a corresponding subset of course schema elements of the generic schema and fine schema elements from the first set of domain data and from the second set of domain data which were mapped to course schema elements in the corresponding subset of the generic schema, and wherein different language understanding models correspond to different subsets of course schema elements;
and
providing an interface to view the plurality of language understanding models with the first domain and second domain.

5 more elements

A computer-readable media storing computer executable instructions that when executed cause a computing system to perform a method of configuring language understanding models, the method comprising:

receiving a request to create a generic schema;
collecting schema data associated with a first language understanding model and associated with a second language understanding model, wherein collecting schema data comprises a first set of domain data for a first domain identifier from a first domain and a second set of domain data from a second domain for a second domain identifier;
identifying a commonality of category between a first fine schema element in the first set of domain data and a second fine schema element in the second set of domain data;
mapping, in response to identifying the commonality, the first fine schema element and the second fine schema element to a third course schema element, wherein the third course schema element describes the identified commonality;
generating a generic schema using the collected schema data, wherein generating the generic schema comprises applying, to the generic schema, the mapping of the first fine schema element and the second fine schema element to the third course schema element;
using the generic schema data to train a plurality of language understanding models, wherein the training enables each of the plurality of language understanding models to process requests relating to the first domain and the second domain based on the mapping, wherein each of the plurality of language understanding models is trained using only a corresponding subset of course schema elements of the generic schema and fine schema elements from the first set of domain data and from the second set of domain data which were mapped to course schema elements in the corresponding subset of the generic schema, and wherein different language understanding models correspond to different subsets of course schema elements;
and
providing an interface to view the plurality of language understanding models with the first domain and second domain.

5 more elements

Dependencies are inferred from the claim text.

Facts

Application: 17/549,966Filed 14 Dec 2021
Priority: 22 Jan 2016
Published: 31 Mar 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification8 codes

G06F 40/58
Processing or translation of natural language: use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for…
G06F 16/212
Schema design and management: with details for data modelling support
G06F 40/30
Handling natural language data: semantic analysis
G06N 20/00
Machine learning