Abstract: In one embodiment, a computer-implemented method includes training, using an artificial intelligence engine, one or more machine learning models using training data comprising identities of writers of content items as input and to output a dataset comprising identities of publishers and a respective probability that each identity of a publisher, from the identities of publishers, is associated with a respective identity of a writer from the identities of writers; receiving, via the one or more machine learning models, a first identity of a first writer; inputting the first identity of the first writer into the one or more machine learning models; outputting, via the one or more machine learning models, the dataset comprising the identities of publishers and the respective probability that each identity of the publisher, from the identities of publishers, is associated with the respective identity of the writer from the identities of writers.

Abstract: In one embodiment, a computer-implemented method is disclosed. The method includes receiving a first content item, transcribing audio included in the first content item to obtain text associated with the audio, determining a plurality of keywords included in the text, classifying, based on the plurality of keywords, the text as one or more nodes in a data structure, and ranking, based on a plurality of factors, the one or more nodes relative to one or more other nodes associated with a second content item.