1. A method comprising: accessing seed metadata, the seed metadata describing a seed, the seed being a basis on which a station library is to be defined; generating a station descriptor profile based on the seed metadata, the station descriptor profile defining a genre composition of the station library; generating a candidate set based on the seed metadata, the candidate set comprising a plurality of candidate media files; for each candidate media file in the candidate set: computing a similarity score associated with the candidate media file, the similarity score including a measure of similarity between the candidate media file and the station descriptor profile; computing one or more boost values associated with the candidate media file based on candidate metadata describing the candidate media file; and computing a relevancy score associated with the candidate media file based on the similarity score and the one or more boost values associated with the candidate media file, the relevancy score providing a basis for selecting the candidate media file for inclusion in the station library; and machine-generating a station set including a portion of the candidate set selected based on the relevancy scores associated with the plurality of candidate media files included in the candidate set, the machine-generated station set defining the station library by referencing each candidate media file in the portion of the candidate set, wherein the station descriptor profile includes one or more focus genre profiles and each candidate media file includes a file genre profile, the one or more focus genre profiles and the file genre profile each including respective multiple genre values and a weight assigned to each genre value, each genre value corresponding to a genre, each weight indicating a percentage of the corresponding genre value relative to the other genre values in the respective multiple genre values, and computing the similarity score associated with the candidate media file includes: computing one or more focus-level similarity scores by comparing, for each focus genre profile in the station descriptor profile: (a) the respective multiple genre values and the corresponding weights of the focus genre profile, and (b) the respective multiple genre values and the corresponding weights of the file genre profile of the candidate media file; and selecting the highest focus-level similarity score to be the similarity score associated with the candidate media file.