TRAINING MACHINE LEARNING MODELS USING CUSTOMER INTERACTION DATA

Abstract

A computer-implemented method includes accessing natural language dialogue data gathered from interactions between an entity and a user. The method further includes accessing contextual information related to the user, which provides additional indications of the user's consumption of the service. The method further includes training a machine learning model to generate structured data that is assembled according to a schema that prepares the structured data for aggregation into clusters, training the machine learning model to aggregate the data into clusters, where each cluster includes an identified standard that defines inclusion in the cluster, training the machine learning model to map the aggregated, structured data to a specified technical issue related to the service that is to be resolved and, based on the mapping, providing an indication of the specified technical issue that is to be resolved to a computing device. Various other methods, systems, and computer-readable media are also disclosed.

CPC Classifications