Method and System of Utilizing Unsupervised Learning to Improve Text to Content Suggestions

A method for training a text-to-content suggestion ML model, the method comprising:

• accessing a dataset containing unlabeled training data collected from an application, the unlabeled training data including at least one of an unordered set of words or data that is partially masked;
• and
• applying an unsupervised ML model to the dataset to generate a pretrained embedding;
• wherein the pretrained embedding is configured to be used to train the text-to-content suggestion ML model utilized by the application.

A non-transitory computer readable medium on which are stored instructions that, when executed, cause a programmable device to:

• access a dataset containing unlabeled training data collected from an application, the unlabeled training data including at least one of an unordered set of words or data that is partially masked;
• and
• apply an unsupervised machine-learning (ML) model to the dataset to generate a pretrained embedding;
• wherein the pretrained embedding is configured to be used to train a text-to-content suggestion ML model utilized by the application.