Abstract:
A network element (200) receives (101), from a plurality of different end users (205), information regarding content clips as pertain to audio-visual content and uses (102) that information to automatically infer a relative popularity of audio-visual content as corresponds to the content clips to provide popularity information. Such audio-visual content can comprise, for example, televised content. The aforementioned information can comprise, for example, such items as a start time and a stop time for a given one of the content clips, at least a portion of a given one of the content clips, a content identifier of some kind, and so forth.
Abstract:
A network element (200) receives (101), from a plurality of different end users (205), information regarding content clips as pertain to audio-visual content and uses (102) that information to automatically infer a relative popularity of audio-visual content as corresponds to the content clips to provide popularity information. Such audio-visual content can comprise, for example, televised content. The aforementioned information can comprise, for example, such items as a start time and a stop time for a given one of the content clips, at least a portion of a given one of the content clips, a content identifier of some kind, and so forth.
Abstract:
A network element (400) can receive (101) (from an end user (404) and via a data network (403)) a message as regards an aggregation of multiple different renderable content items. By one approach this message comprises, at least in part, selection criteria as have been selected by the end user. This network element can then automatically use (102) this selection criteria to select a plurality of specific renderable content items from amongst a plurality of candidate different renderable content items. These teachings will then support automatically combining (103) the plurality of specific renderable content items to form the requested aggregation of multiple different renderable content items.