Abstract: The present systems and methods relate to a concept for providing recommendations targeted to particular, “subject” user. The present systems and methods involve obtaining historical usage data associated with the subject user; identifying candidate users; calculating media preference overlap scores with respect to the subject user and each candidate user; ranking the candidate user according to their preference overlap scores, and generating recommendations for the subject user from the historical usage data associated with the candidate users.

Abstract: Media-presentation-conscious scheduling protocols are disclosed that may associate a geographical location containing a thing with an identifier of the thing and allow later-found media works that pertain to the identifier to be presented at a mobile device before the device reaches a waypoint of the location. Alternatively or additionally, such protocols may respond to a predicted connectivity impairment of a traveling device by obtaining supplemental content to mitigate a predicted capacity shortage. Alternatively or additionally, such protocols may interrupt live stream content, insert on-demand content, and later return to live stream presentation automatically.

Abstract: Provided herein are systems and methods for generating a set of recommended media works based on an identified seed media work. The seed media work is used to identify a set of co-occurring media works, which are defined as media works that have been intentionally interacted with within a predetermined time window as the seed media work by a single user. After the co-occurrence set is created, it is ranked and filtered. Media works identified in the co-occurrence set may then be selected based on their ranking.

Abstract: The present systems and methods relate to a concept for providing recommendations targeted to particular, “subject” user. The present systems and methods involve obtaining historical usage data associated with the subject user; identifying candidate users; calculating media preference overlap scores with respect to the subject user and each candidate user; ranking the candidate user according to their preference overlap scores, and generating recommendations for the subject user from the historical usage data associated with the candidate users.

Abstract: The present systems and methods relate to a concept for providing media recommendations targeted to particular, “subject” user. The present systems and methods involve obtaining historical usage data associated with the subject user; identifying candidate users; calculating media preference overlap scores with respect to the subject user and each candidate user; ranking the candidate user according to their media preference overlap scores, and generating recommendations for the subject user from the historical usage data associated with the candidate users.

Abstract: The present systems and methods relate to a concept for providing media recommendations targeted to particular, “subject” user. The present systems and methods involve obtaining historical usage data associated with the subject user; identifying candidate users; calculating media preference overlap scores with respect to the subject user and each candidate user; ranking the candidate user according to their media preference overlap scores, and generating recommendations for the subject user from the historical usage data associated with the candidate users.

Abstract: Provided herein are systems and methods for generating a set of recommended media works based on an identified seed media work. The seed media work is used to identify a set of co-occurring media works, which are defined as media works that have been intentionally interacted with within a predetermined time window as the seed media work by a single user. After the co-occurrence set is created, it is ranked and filtered. Media works identified in the co-occurrence set may then be selected based on their ranking.