Automated content recognition machine learning model generation

A method, comprising:

• receiving, from a user computing device comprising one or more processors and memory, user input data indicative of a new attribute of video content for adding labels to video data stored in a database of video data, wherein the video data stored in the database is not currently labelled for the new attribute, wherein the input data is further indicative of a type of machine learning model to be trained to label video data having the new attribute;
• determining embedding values for a machine learning model of the type of machine learning model based on the user input data indicative of the new attribute;
• determining a first subset of data having a similarity to the new attribute from a database of video data based on the user input data and the embedding values, wherein the video data of the database is labelled with previously determined labels according to one or more attributes different from the new attribute and is not currently labelled for the new attribute;
• receiving indications of matching for the first subset of data, the indications of matching associated with whether an instance of the first subset of data is associated with the new attribute;
• determining a training dataset, from the first subset of data, based on the indications of matching;
• generating a trained machine learning model to label video data having the new attribute by training the machine learning model using the training dataset;
• determining labels for a second subset of data using the trained machine learning model;
• determining a precision of the trained machine learning model based on the labels for the second subset of data and label verification data that indicates whether the labels are accurately applied to the second subset of data;
• performing at least one of:
• further training the trained machine learning model using the label verification data in response to the precision being below a threshold;
• or
• generating an alert that the trained machine learning model is trained in response to the precision being equal to or above the threshold;
• using the trained machine learning model to identify video data in the database having the new attribute;
• and
• storing indications of labels for the new attribute associated with the identified video data within the database such that labelling of the video data of the database is updated according to the new attribute and continues to provide the previously determined labels for the one or more attributes different from the new attribute.