Systems for Role Classification

In a digital medium environment to train a first machine learning model for role classification, a system comprising:

• at least one computing device;
• and
• a role module implemented at least partially in hardware of the at least one computing device to:
• receive a first set of training data including a training classification and training feature values of features, the training features values generated by a second machine learning model by processing a corpus of text associated with an ID and the training classification is indicative of a relationship of the ID with respect to a product or service;
• generate a candidate classification by processing the training feature values using the first machine learning model;
• and
• train the first machine learning model by comparing the candidate classification to the training classification using a first loss function.

A system comprising:

• a compilation module implemented at least partially in hardware of a computing device to:
• receive a user input defining a user ID for role classification;
• and
• compile a corpus of text associated with the user ID;
• a feature module implemented at least partially in the hardware of the computing device to generate feature values of features by processing the corpus of text, the features representing questions with respect to the corpus of text and the feature values representing answers to the questions included in the corpus of text;
• a classification module implemented at least partially in the hardware of the computing device to generate a classification of a role by processing the feature values, the classification of the role indicating a relationship of the user ID with respect to a product or service;
• and
• a display module implemented at least partially in the hardware of the computing device to output an indication of the classification of the role for display in a user interface.