US 2025/0232137 A1 · CREATING PREDICTOR VARIABLES FOR PREDICTION MODELS FROM UNSTRUCTURED DATA USING NATURAL LANGUAGE PROCESSING

Abstract

Systems and methods for creating predictor variables from unstructured data for prediction models are provided. A variable creation application receives unstructured data and processing the unstructured data to generate processed data. Based on the processed data, the variable creation application generates an attribute pool that contains multiple predictor variables generated by applying natural language processing (NLP) procedures on the processed data. The variable creation application further executes a prediction model on at least the predictor variables in the attribute pool to generate a prediction result. Based on the prediction result, the variable creation application evaluates the predictive power of each of the predictor variables and retains predictor variables that are predictive as input predictor variables for the prediction model.

Claims20

Dependent claims

A computer-implemented method in which one or more processing devices performs operations comprising:

accessing unstructured data;
generating a plurality of predictor variables by applying one or more natural language processing (NLP) procedures on the unstructured data;
generating an attribute pool that comprises the generated plurality of predictor variables;
executing a machine-learning prediction model on at least the plurality of predictor variables in the attribute pool to generate a prediction result;
evaluating a predictive power of each of the plurality of predictor variables based on the prediction result;
retaining at least one predictor variable among the plurality of predictor variables that is predictive as an input predictor variable for the machine-learning prediction model;
training the machine-learning prediction model trained using predictor variables comprising the at least one predictor variable;
and
transmitting, to a remote computing device, a risk indicator for a target entity generated by the trained machine-learning prediction model, wherein the risk indicator is usable for controlling access to one or more interactive computing environments by the target entity.

6 more elements

A system for generating predictor variables from unstructured data, the system comprising:

one or more processing device;
and
one or more non-transitory computer-readable medium communicatively coupled to the one or more processing device, wherein the one or more processing devices are configured to execute program code stored in the non-transitory computer-readable medium and thereby perform operations comprising:
processing the unstructured data to generate processed data;
generating a plurality of predictor variables by applying one or more natural language processing (NLP) procedures on the processed data;
generating an attribute pool that comprises the generated plurality of predictor variables;
executing a prediction model on at least the plurality of predictor variables in the attribute pool to generate a prediction result;
evaluating a predictive power of each of the plurality of predictor variables based on the prediction result;
and
retaining at least one predictor variable among the plurality of predictor variables that is predictive as an input predictor variable for the prediction model.

7 more elements

A computer-readable medium having instructions stored thereon that are executable by a processor to causing a computing device to perform operations, the operations comprising:

accessing unstructured data;
processing the unstructured data to generate processed data;
generating a plurality of predictor variables by applying one or more natural language processing (NLP) procedures on the processed data;
generating an attribute pool that comprises the generated plurality of predictor variables;
executing a prediction model on at least the plurality of predictor variables in the attribute pool to generate a prediction result;
evaluating a predictive power of each of the plurality of predictor variables based on the prediction result;
and
retaining at least one predictor variable among the plurality of predictor variables that is predictive as an input predictor variable for the prediction model.

5 more elements

Dependencies are inferred from the claim text.

Creating predictor variables for prediction models from unstructured data using natural language processing

Life of this patent

Creating predictor variables for prediction models from unstructured data using natural language processing

Life of this patent

Abstract

Claims20