Methods and Systems for Personalizing Content in Accordance with Divergences in a User's Listening History

A method, comprising:

• at an electronic device associated with a media-providing service and having one or more processors and memory storing instructions for execution by the one or more processors:
• accessing a listening history of a user of the media-providing service;
• for each characteristic of a set of characteristics describing tracks provided by the media-providing service, determining, for the user, a measure of divergence indicating a degree of lack of uniformity in the listening history of the user with respect to listening contexts, the determining including normalizing, based on the listening history, a calculated divergence for the characteristic relative to measures of divergence of other users in the listening contexts, wherein each characteristic has a plurality of possible values;
• identifying a characteristic, of the set of characteristics, having a respective measure of divergence that satisfies a threshold indicative of the lack of uniformity in the listening history with respect to the listening contexts;
• determining a representative value of the identified characteristic for a listening context corresponding to a current listening context of the user;
• in the current listening context, providing personalized content to a client device of the user based on the representative value of the identified characteristic, including providing a recommended playlist that includes tracks having the representative value of the identified characteristic for the listening context corresponding to the current listening context;
• and
• streaming one or more tracks within the recommended playlist to the client device of the user.

An electronic device, comprising:

• one or more processors;
• and
• memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for:
• accessing a listening history of a user of a media-providing service;
• for each characteristic of a set of characteristics describing tracks provided by the media-providing service, determining, for the user, a measure of divergence indicating a degree of lack of uniformity in the listening history of the user with respect to listening contexts, the determining including normalizing, based on the listening history, a calculated divergence for the characteristic relative to measures of divergence of other users in the listening contexts, wherein each characteristic has a plurality of possible values;
• identifying a characteristic, of the set of characteristics, having a respective measure of divergence that satisfies a threshold indicative of the lack of uniformity in the listening history with respect to the listening contexts;
• determining a representative value of the identified characteristic for a listening context corresponding to a current listening context of the user;
• in the current listening context, providing personalized content to a client device of the user based on the representative value of the identified characteristic, including providing a recommended playlist that includes tracks having the representative value of the identified characteristic for the listening context corresponding to the current listening context;
• and
• streaming one or more tracks within the recommended playlist to the client device of the user.

A non-transitory computer-readable storage medium, storing one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for:

• accessing a listening history of a user of a media-providing service;
• for each characteristic of a set of characteristics describing tracks provided by the media-providing service, determining, for the user, a measure of divergence indicating a degree of lack of uniformity in the listening history of the user with respect to listening contexts, the determining including normalizing, based on the listening history, a calculated divergence for the characteristic relative to measures of divergence of other users in the listening contexts, wherein each characteristic has a plurality of possible values;
• identifying a characteristic, of the set of characteristics, having a respective measure of divergence that satisfies a threshold indicative of the lack of uniformity in the listening history with respect to the listening contexts;
• determining a representative value of the identified characteristic for a listening context corresponding to a current listening context of the user;
• in the current listening context, providing personalized content to a client device of the user based on the representative value of the identified characteristic, including providing a recommended playlist that includes tracks having the representative value of the identified characteristic for the listening context corresponding to the current listening context;
• and
• streaming one or more tracks within the recommended playlist to the client device of the user.