1. A method, comprising: assembling, via a processor, an input data set based on performance data of delivered invitational content with respect to known contexts, content similarity data for the delivered invitational content, and context similarity data for the known contexts; identifying clusters in the input data set, each of the clusters associating at least one of the delivered invitational content and at least one of the known contexts; generating first rank values for the clusters with respect to at least one of the delivered invitational content and second rank values for the clusters with respect to at least one of the known contexts; computing total rank values for the identified known contexts, wherein for each of the identified known contexts the computing comprises: identifying one or more rank paths associated with the one of the identified known contexts, calculating a product of first and second rank values associated with each of the one or more rank paths, and calculating a total rank value for the one of the identified known contexts as a sum of the rank path products for each of the one or more rank paths; and storing a dataset for a database, the dataset comprising at least the delivered invitational content, the known contexts, the identified clusters, the first rank values, the second rank values, the total rank values, content metadata for the delivered invitational content, and context metadata for the known contexts.
1. A method, comprising: assembling, via a processor, an input data set based on performance data of delivered invitational content with respect to known contexts, content similarity data for the delivered invitational content, and context similarity data for the known contexts; identifying clusters in the input data set, each of the clusters associating at least one of the delivered invitational content and at least one of the known contexts; generating first rank values for the clusters with respect to at least one of the delivered invitational content and second rank values for the clusters with respect to at least one of the known contexts; computing total rank values for the identified known contexts, wherein for each of the identified known contexts the computing comprises: identifying one or more rank paths associated with the one of the identified known contexts, calculating a product of first and second rank values associated with each of the one or more rank paths, and calculating a total rank value for the one of the identified known contexts as a sum of the rank path products for each of the one or more rank paths; and storing a dataset for a database, the dataset comprising at least the delivered invitational content, the known contexts, the identified clusters, the first rank values, the second rank values, the total rank values, content metadata for the delivered invitational content, and context metadata for the known contexts. 7. The method of claim 1 , further comprising: generating an ordered list of delivered content items for a candidate context based on the clusters, the first rank values, and the second rank values.