Auto-classification system and method with dynamic user feedback

A computer program product for automatic classification of digital content, the computer program product comprising a non-transitory computer-readable medium storing instructions translatable by a processor of an auto-classification system for:

• creating or modifying a classification model, the creating or modifying comprising importing, from a document source into the classification model, example documents having content that exemplifies a content category or classification such that the classification model comprises the example documents thus imported;
• testing the classification model for accuracy assessment, the testing comprising classifying test documents utilizing the classification model;
• generating, based on the testing, feedback on the accuracy assessment of the classification model;
• displaying, through a user interface on a user device, the feedback on the accuracy assessment of the classification model;
• determining, based on an indication received through the user interface, whether to refine the classification model, the indication received through the user interface including an instruction to reject or accept the content category or classification of the example documents imported into the classification model;
• responsive to the indication indicating user refinement of the classification model, iteratively performing the modifying, the testing, the generating, the displaying, and the determining;
• classifying, utilizing the classification model, documents in a repository, the classifying comprising:
• comparing a document in the repository to a set of example documents in the classification model;
• and
• assigning the content category or classification of the set of example documents in the classification model to the document in the repository.

An auto-classification system for automatic classification of digital content, the auto-classification system comprising:

• a processor;
• a non-transitory computer-readable medium;
• and
• stored instructions translatable by the processor for:
• creating or modifying a classification model, the creating or modifying comprising importing, from a document source into the classification model, example documents having content that exemplifies a content category or classification such that the classification model comprises the example documents thus imported;
• testing the classification model for accuracy assessment, the testing comprising classifying test documents utilizing the classification model;
• generating, based on the testing, feedback on the accuracy assessment of the classification model;
• displaying, through a user interface on a user device, the feedback on the accuracy assessment of the classification model;
• determining, based on an indication received through the user interface, whether to refine the classification model, the indication received through the user interface including an instruction to reject or accept the content category or classification of the example documents imported into the classification model;
• responsive to the indication indicating user refinement of the classification model, iteratively performing the modifying, the testing, the generating, the displaying, and the determining;
• classifying, utilizing the classification model, documents in a repository, the classifying comprising:
• comparing a document in the repository to a set of example documents in the classification model;
• and
• assigning the content category or classification of the set of example documents in the classification model to the document in the repository.