Abstract: Personalized media charts are described. In embodiments, a request can be received for a personalized media chart that lists media assets as recommendations in a relevant order for a user. The media assets are initially ordered in the personalized media chart according to a chart rank for each media asset. A relevance factor is then determined for each of the media assets, where the relevance factor for a media asset indicates a relevance of the media asset to the user. A chart rank adjustment is calculated for each of the media assets based on the relevance factors for each of the media assets, and the media assets are then reordered in the personalized media chart according to the chart rank adjustments for each of the media assets.

Abstract: Systems and methods for personalized media recommendation are provided. One example system may include a media server including a media database containing a plurality of media tracks and a database schema defining multiple media styles. The media server may further include a media delivery engine configured to transmit media tracks to each of a plurality of media clients. The system may further include a feedback module configured to receive history data from each of the media clients. Further still, the system may include a recommendation engine configured to compute a plurality of user-specific style weights, and to select one or more recommended media tracks for each user, The recommendation engine may be further configured to send a recommendation message to the media client including media links to the recommended media tracks on the media server, to cause the media client to display the media links to a user.

Abstract: Personalized media charts are described. In embodiments, a request can be received for a personalized media chart that lists media assets as recommendations in a relevant order for a user. The media assets are initially ordered in the personalized media chart according to a chart rank for each media asset. A relevance factor is then determined for each of the media assets, where the relevance factor for a media asset indicates a relevance of the media asset to the user. A chart rank adjustment is calculated for each of the media assets based on the relevance factors for each of the media assets, and the media assets are then reordered in the personalized media chart according to the chart rank adjustments for each of the media assets.

Abstract: Embodiments are disclosed herein that relate to the presentation of an entertainment consumption history via a timeline. For example, one embodiment comprises receiving entertainment consumption history comprising one or more entertainment content identifiers each identifying one or more entertainment content items sent to a selected user. The entertainment consumption history also comprises, for each entertainment content identifier, information related to a time at which the one or more entertainment content items identified by the entertainment content identifier were sent to the selected user. The embodiment further comprises sending to a display device a graphical depiction of the entertainment consumption history data as a timeline with each entertainment content identifier being illustrated along a direction of a time axis at a location representative of the time at which the one or more entertainment content items represented by the entertainment content identifier were sent to the selected user.

Abstract: Systems and methods for personalized media recommendation are provided. One example system may include a media server including a media database containing a plurality of media tracks and a database schema defining multiple media styles. The media server may further include a media delivery engine configured to transmit media tracks to each of a plurality of media clients. The system may further include a feedback module configured to receive history data from each of the media clients. Further still, the system may include a recommendation engine configured to compute a plurality of user-specific style weights, and to select one or more recommended media tracks for each user, The recommendation engine may be further configured to send a recommendation message to the media client including media links to the recommended media tracks on the media server, to cause the media client to display the media links to a user.