Utilizing machine-learning models to generate identifier embeddings and determine digital connections between digital content items

A non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause a computing device to:

• identify a plurality of identifiers corresponding to a plurality of digital content items, wherein the plurality of identifiers comprise a plurality of filenames associated with the plurality of digital content items;
• generate a plurality of identifier embeddings corresponding to the plurality of identifiers by utilizing one or more embedding machine-learning models;
• generate digital similarity predictions between the plurality of digital content items by processing the plurality of identifier embeddings utilizing a content management model;
• and
• determine a digital connection between a first digital content item and a second digital content item from the plurality of digital content items based on the digital similarity predictions.

A computer-implemented method comprising:

• identifying a plurality of identifiers corresponding to a plurality of digital content items;
• generating a plurality of identifier embeddings corresponding to the plurality of identifiers by utilizing one or more embedding machine-learning models;
• generating digital similarity predictions between the plurality of digital content items by processing the plurality of identifier embeddings utilizing a content management model;
• and
• determining a digital connection between a subset of digital content items of the plurality of digital content items based on the digital similarity predictions.