Generation of digital standards using machine-learning model
One embodiment provides a method for generating a digital standard utilizing a trained machine-learning model, the method including: training at least one machine-learning model to generate digital standards from underlying standards utilizing a schema, wherein the training includes: receiving, for unstructured information within the underlying standards, a plurality of annotated underlying standards including a set of underlying standards having annotations identifying a classification of conceptual units within the set of underlying standards and corresponding to the schema; and teaching, for structured information within the underlying standards, the at least one machine-learning model patterns delineating information as belonging to conceptual units within the schema; and deploying the at least one trained machine-learning model to convert a second set of underlying standards to the digital standards, wherein the second set of underlying standards is different than the set of underlying standards. Other aspects are described and claimed.
1 . A method for generating a digital standard utilizing a trained machine-learning model, the method comprising:
training at least one machine-learning model to generate digital standards from underlying standards utilizing a schema that identifies a format of a digital standard and provides a functionality to the digital standard, wherein the training comprises:
receiving, for unstructured information within the underlying standards, a plurality of annotated underlying standards comprising a set of underlying standards having annotations identifying a classification of conceptual units within the set of underlying standards and corresponding to the schema; and
teaching, for structured information within the underlying standards, the at least one machine-learning model patterns delineating information as belonging to conceptual units within the schema; and
deploying the at least one trained machine-learning model to convert a second set of underlying standards to the digital standards, wherein the second set of underlying standards is different than the set of underlying standards.
2 . The method of claim 1 , wherein the schema identifies a format of the digital standard and provides a functionality to the digital standard.
3 . The method of claim 1 , wherein the conceptual units comprise a unit of information contained within the set of underlying standard.
4 . The method of claim 1 , wherein the training comprises training the machine-learning model to recognize contextual information surrounding a conceptual unit.
5 . The method of claim 1 , wherein the receiving a plurality of annotated underlying standards comprises extracting, using the at least one machine-learning model and during the training, conceptual units from the plurality of annotated underlying standards and accessing an annotation corresponding to each of the extracted conceptual units.
6 . The method of claim 1 , wherein the teaching comprises extracting, using the at least one machine-learning model and during the training, information within the structured information and accessing a classification corresponding to the information.
7 . The method of claim 1 , wherein the training comprises training the at least one machine-learning model utilizing regular expression patterns.
8 . The method of claim 1 , comprising classifying, utilizing the at least one trained machine-learning model, extracted conceptual units from the second set of underlying standards based upon the schema and storing the classifying conceptual units into a data repository as defined by the schema.
9 . The method of claim 1 , comprising displaying a digital standard corresponding to a selected of the second set of underlying standard in a digital standard user interface.
10 . The method of claim 1 , comprising refining the at least one trained machine-learning model utilizing subsequently classified extracted conceptual units.
11 . A system for generating a digital standard utilizing a trained machine-learning model, the system comprising:
one or more processors;
a memory device that stores instructions executable by the processor to:
train at least one machine-learning model to generate digital standards from underlying standards utilizing a schema that identifies a format of a digital standard and provides a functionality to the digital standard, wherein the training comprises:
receiving, for unstructured information within the underlying standards, a plurality of annotated underlying standards comprising a set of underlying standards having annotations identifying a classification of conceptual units within the set of underlying standards and corresponding to the schema; and
teaching, for structured information within the underlying standards, the at least one machine-learning model patterns delineating information as belonging to conceptual units within the schema; and
deploy the at least one trained machine-learning model to convert a second set of underlying standards to the digital standards, wherein the second set of underlying standards is different than the set of underlying standards.
12 . The system of claim 11 , wherein the schema identifies a format of the digital standard and provides a functionality to the digital standard.
13 . The system of claim 11 , wherein the conceptual units comprise a unit of information contained within the set of underlying standard.
14 . The system of claim 11 , wherein the training comprises training the machine-learning model to recognize contextual information surrounding a conceptual unit.
15 . The system of claim 11 , wherein the receiving a plurality of annotated underlying standards comprises extracting, using the at least one machine-learning model and during the training, conceptual units from the plurality of annotated underlying standards and accessing an annotation corresponding to each of the extracted conceptual units.
16 . The system of claim 11 , wherein the teaching comprises extracting, using the at least one machine-learning model and during the training, information within the structured information and accessing a classification corresponding to the information.
17 . The system of claim 11 , wherein the training comprises training the at least one machine-learning model utilizing regular expression patterns.
18 . The system of claim 11 , comprising displaying a digital standard corresponding to a selected of the second set of underlying standard in a digital standard user interface.
19 . The system of claim 11 , comprising refining the at least one trained machine-learning model utilizing subsequently classified extracted conceptual units.
20 . A product for generating a digital standard utilizing a trained machine-learning model, the product comprising:
a storage device that stores code, the code being executable by one or more processors and comprising:
code that trains at least one machine-learning model to generate digital standards from underlying standards utilizing a schema that identifies a format of a digital standard and provides a functionality to the digital standard, wherein the training comprises:
receiving, for unstructured information within the underlying standards, a plurality of annotated underlying standards comprising a set of underlying standards having annotations identifying a classification of conceptual units within the set of underlying standards and corresponding to the schema; and
teaching, for structured information within the underlying standards, the at least one machine-learning model patterns delineating information as belonging to conceptual units within the schema; and
code that deploys the at least one trained machine-learning model to convert a second set of underlying standards to the digital standards, wherein the second set of underlying standards is different than the set of underlying standards.