Abstract: A server system receives a request to generate a playlist. The playlist includes a sequence of media items. The server system receives a plurality of constraints that define disqualification criteria for excluding media items from a respective slot in the sequence of media items. The plurality of constraints for the respective slot in the sequence of media items includes at least one constraint that is based on already-populated slots in the sequence of media items. The server system generates the playlist by sequentially populating each respective slot in the sequence of media items, including selecting, for the respective slot, a respective media item that meets the plurality of constraints for the respective slot in the sequence of media items. The server system provides the playlist to a user of the media providing service.

Abstract: A computer system associated with a media-providing service obtains a set of text descriptors from a plurality of media items in a pool of media items personalized for a first user. The system selects, from the set of text descriptors, a first text descriptor using first criteria and a second text descriptor using second criteria. The system causes an application associated with the media-providing service, executing on a client device of the first user, to concurrently display a first option for playing back a first playlist of media items associated with the first text descriptor and a second option for playing back a second playlist of media items associated with the second text descriptor. In response to receiving selection by the first user of the first option, the system provides, to the application, media items from the first playlist of media items associated with the first text descriptor.

Abstract: The various implementations described herein include methods and devices for identifying and presenting content to users. In one aspect, a method includes providing a domain specific language (DSL) tool to a user of the computing device and receiving a plurality of user inputs via the DSL tool. The plurality of user inputs includes: an input identifying a DSL object corresponding to a media pool; an input identifying a DSL object corresponding to a mutator to be applied to the media pool; and inputs identifying a plurality of DSL objects corresponding to respective objectives for a media set list. The method also includes generating the media set list from the media pool based on the mutator and the objectives and presenting information about the generated media set list to the user.

Abstract: A method for personalizing media content for a user is provided. The method includes, at an electronic device, streaming a first media item from a first set of media items, the first set of media items compiled using a first recommendation hypothesis. The method further includes, while streaming the first media item, in response to a first user request, selecting, without user intervention, a second set of media items, distinct from the first set of media items, including determining a presentation order of a plurality of sets of media items using a heuristic applied to the plurality of sets of media items. The second set of media items is compiled using a second recommendation hypothesis, wherein the second recommendation hypothesis is distinct from the first recommendation hypothesis. The method includes streaming a second media item from the second set of media items.

Abstract: The various implementations described herein include methods and devices for identifying and presenting content to users. In one aspect, a method includes providing a domain specific language (DSL) tool to a user of the computing device and receiving a plurality of user inputs via the DSL tool. The plurality of user inputs includes: an input identifying a DSL object corresponding to a media pool; an input identifying a DSL object corresponding to a mutator to be applied to the media pool; and inputs identifying a plurality of DSL objects corresponding to respective objectives for a media set list. The method also includes generating the media set list from the media pool based on the mutator and the objectives and presenting information about the generated media set list to the user.

Abstract: A method for personalizing media content for a user is provided. The method includes, at an electronic device, streaming a first media item from a first set of media items, the first set of media items compiled using a first recommendation hypothesis. The method further includes, while streaming the first media item, in response to a first user request, selecting, without user intervention, a second set of media items, distinct from the first set of media items, including determining a presentation order of a plurality of sets of media items using a heuristic applied to the plurality of sets of media items. The second set of media items is compiled using a second recommendation hypothesis, wherein the second recommendation hypothesis is distinct from the first recommendation hypothesis. The method includes streaming a second media item from the second set of media items.

Abstract: A media content item recommendation system recommends media content items based on one or more attributes of a seed playlist. The recommended media content items can be determined from a plurality of existing playlists that have been created over a period of time. Such existing playlists can be selected based on similarity to the seed playlist.

Abstract: Methods, systems, and computer programs for generating a playlist of media content items that are popular with the friends of the first user. A first user taste profile is determined and a user taste profile is determined for each of a plurality of social connections. A similarity score is calculated between the first user taste profile and the user taste profile of each social connection. Media content items consumed by social connections with the highest similarity score are selected and placed in a playlist for the first user.

Abstract: A media content item recommendation system recommends media content items based on one or more attributes of a seed playlist. The recommended media content items can be determined from a plurality of existing playlists that have been created over a period of time. Such existing playlists can be selected based on similarity to the seed playlist.

Abstract: A descriptive media content search solution is provided to allow a user to search for media content that better matches a user's descriptive search request. The descriptive media content search solution utilizes an extensive catalog of playlists each having a playlist description, such as a playlist title or other descriptive text, and identifies additional descriptive information for media content items to be searched. The descriptive media content search solution can set up a descriptive search database and utilize the descriptive search database to conduct a descriptive search responsive to the user's descriptive search request.

Abstract: A method for personalizing media content for a user is provided. The method includes, at an electronic device, streaming a first media item from a first set of media items, the first set of media items compiled using a first recommendation hypothesis. The method further includes, while streaming the first media item, in response to a first user request, selecting, without user intervention, a second set of media items, distinct from the first set of media items, including determining a presentation order of a plurality of sets of media items using a heuristic applied to the plurality of sets of media items. The second set of media items is compiled using a second recommendation hypothesis, wherein the second recommendation hypothesis is distinct from the first recommendation hypothesis. The method includes streaming a second media item from the second set of media items.

Abstract: A server system receives a request to generate a playlist. The playlist includes a sequence of media items. The server system receives a plurality of constraints that define disqualification criteria for excluding media items from a respective slot in the sequence of media items. The plurality of constraints for the respective slot in the sequence of media items includes at least one constraint that is based on already-populated slots in the sequence of media items. The server system generates the playlist by sequentially populating each respective slot in the sequence of media items, including selecting, for the respective slot, a respective media item that meets the plurality of constraints for the respective slot in the sequence of media items. The server system provides the playlist to a user of the media providing service.

Abstract: A descriptive media content search solution is provided to allow a user to search for media content that better matches a user's descriptive search request. The descriptive media content search solution utilizes an extensive catalog of playlists each having a playlist description, such as a playlist title or other descriptive text, and identifies additional descriptive information for media content items to be searched. The descriptive media content search solution can set up a descriptive search database and utilize the descriptive search database to conduct a descriptive search responsive to the user's descriptive search request.

Abstract: Methods, systems, and computer programs for generating a playlist of media content items that are popular with the friends of the first user. A first user taste profile is determined and a user taste profile is determined for each of a plurality of social connections. A similarity score is calculated between the first user taste profile and the user taste profile of each social connection. Media content items consumed by social connections with the highest similarity score are selected and placed in a playlist for the first user.

Abstract: Methods, systems, and computer programs for generating a playlist of media content items that are popular with the friends of the first user. A first user taste profile is determined and a user taste profile is determined for each of a plurality of social connections. A similarity score is calculated between the first user taste profile and the user taste profile of each social connection. Media content items consumed by social connections with the highest similarity score are selected and placed in a playlist for the first user.

Abstract: A descriptive media content search solution is provided to allow a user to search for media content that better matches a user's descriptive search request. The descriptive media content search solution utilizes an extensive catalog of playlists each having a playlist description, such as a playlist title or other descriptive text, and identifies additional descriptive information for media content items to be searched. The descriptive media content search solution can set up a descriptive search database and utilize the descriptive search database to conduct a descriptive search responsive to the user's descriptive search request.

Abstract: A media content item recommendation system recommends media content items based on one or more attributes of a seed playlist. The recommended media content items can be determined from a plurality of existing playlists that have been created over a period of time. Such existing playlists can be selected based on similarity to the seed playlist.

Abstract: A descriptive media content search solution is provided to allow a user to search for media content that better matches a user's descriptive search request. The descriptive media content search solution utilizes an extensive catalog of playlists each having a playlist description, such as a playlist title or other descriptive text, and identifies additional descriptive information for media content items to be searched. The descriptive media content search solution can set up a descriptive search database and utilize the descriptive search database to conduct a descriptive search responsive to the user's descriptive search request.

Abstract: Methods, systems, and computer programs for generating a playlist of media content items that are popular with the friends of the first user. A first user taste profile is determined and a user taste profile is determined for each of a plurality of social connections. A similarity score is calculated between the first user taste profile and the user taste profile of each social connection. Media content items consumed by social connections with the highest similarity score are selected and placed in a playlist for the first user.

Abstract: A media content item recommendation system recommends media content items based on one or more attributes of a seed playlist. The recommended media content items can be determined from a plurality of existing playlists that have been created over a period of time. Such existing playlists can be selected based on similarity to the seed playlist.