Recommending media items based on purchase history

A server computer comprising:

• at least one processor;
• and
• at least one memory containing instructions that, when executed, cause the at least one processor to:
• receive, via a network, a recommendation request requesting an electronic target-category item be served to a first electronic account;
• determine that electronic target-category preference data associated with the first electronic account is not capable of recommending an electronic music item;
• determine a plurality of source-category preference clusters that are each associated with an electronic source-category preference profile, wherein the source-category preference clusters are created by a first clustering operation that clusters a first population of electronic accounts into the source-category preference clusters based on online source-category preferences of each of the first population of electronic accounts;
• select from the source-category preference clusters a first source-category preference cluster associated with a first electronic source-category preference profile for the first electronic account, wherein the first electronic source-category preference profile corresponds to the first electronic account at a source-category strength level determined from similarities between the first electronic source-category preference profile and source-categories purchased by the first electronic account;
• determine a plurality of target-category preference clusters that are each associated with an electronic target-category preference profile, wherein the target-category preference clusters are created by a second clustering operation that clusters a second population of electronic accounts into target-category preference clusters based on online target-category preference data for the second population of electronic accounts;
• identify a preference relationship between the first source-category preference cluster and a first target-category preference cluster, wherein the preference relationship is associated with a preference relationship strength value that indicates a likelihood that an account within the first source-category preference cluster is also part of the first target-category preference cluster;
• identify a first electronic target-category preference profile for the first target-category preference cluster to be used for recommending target-category items for the first electronic account;
• select at least one target-category item based on the identified first electronic target-category preference profile;
• and
• recommend, based on the recommendation request, the selected at least one target-category item.

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

• receive, via a network, a recommendation request requesting an electronic media item be served to a first electronic account;
• determine that music preference data associated with the first electronic account is unable to recommend an electronic music item;
• create, based on a first clustering operation, a plurality of application preference clusters that are each associated with an electronic application preference profile, wherein the first clustering operation clusters a first population of electronic accounts into the application preference clusters based on software applications purchased online by each of the first population of electronic accounts;
• select, from the application preference clusters, a first application preference cluster associated with a first electronic application preference profile for the first electronic account, wherein the first electronic application preference profile corresponds to the first electronic account at an application preference strength level determined from similarities between the first electronic application preference profile and applications purchased by the first electronic account;
• create, based on a second clustering operation, a plurality of music preference clusters that are each associated with an electronic music preference profile, wherein the second clustering operation clusters a second population of electronic accounts into music preference clusters based on online music preference data for the second population of electronic accounts;
• identify a preference relationship between the first application preference cluster and a first music preference cluster, wherein the preference relationship is associated with a preference relationship strength value that indicates a likelihood that an electronic account within the first application preference cluster is also part of the first music preference cluster;
• identify a first electronic music preference profile for the first music preference cluster to be used for recommending electronic media items for the first electronic account based on the application preference strength level and the preference relationship strength value;
• and
• select at least one electronic music item based on the identified first electronic music preference profile.