Abstract: A system receives information associated with an interaction with an individual in a context. Then, the system analyzes the information to extract features associated with one or more attributes of the individual. Moreover, the system generates, based at least in part on the extracted features, a group of behavioral agents in a multi-layer hierarchy that automatically mimics the one or more attributes. Next, the system calculates one or more performance metrics associated with the group of behavioral agents and the one or more attributes. Furthermore, the system determines, based at least in part on the one or more performance metrics, one or more deficiencies in the extracted features. Additionally, the system selectively acquires second information associated with additional interaction with the individual in the context based at least in part on the one or more deficiencies to at least in part correct for the one or more deficiencies.

Abstract: Large media libraries containing songs, movies, or images, can be organized as a graphical media map. Depending on the contents of a particular large media library, the media map can have empty cells that do not correspond to a media item in the media library. To fill these cells with meaningful recommendations based on media items that are already in the library, a recommendation system provides a recommendation of a media item for a particular cell based on the media items corresponding to cells proximate to the cell. The recommendation is generated using metadata tags describing the nearby media items and media items that are not currently part of the media library. The recommendations can be updated based on changes made to the media map.

Abstract: Libraries containing numerous media items such as movies, music, and still images can be difficult to organize in a meaningful and accessible way. To more efficiently and aesthetically organize media items in a library, media maps are generated from hierarchical trees. The media maps are displayed to a user via a user display device. The user can quickly navigate through the media maps to discover connections and similarities between media items previously unknown to the user. The user can further make changes to the media map by interacting with the media map via a user interface. The media map is then re-generated to reflect the changes made by the user. The user can thus personalize the automatically generated media map to reflect his own media preferences and opinions.

Abstract: Increasingly, large libraries of digital media items such as music, movies, and images are maintained. One way to consume the media items is via playlists. Playlists are an ordered list of some of the media items according to a theme or a progression from one theme to another theme. Systems and methods described herein allow a user to request generation of a playlist via a media map of the media library. The request can be in a variety of forms including: an identification of a region, identifications of starting and ending points, identification of a defined area of the media map, a gesture identifying a path through the media map, and an identification of a metadata tag associated with some of the media items within the media library. Further, branching playlists can be generated from a currently presented media item, which may itself be from a generated playlist.

Abstract: Media items in a media library are organized into a hierarchical tree so that a particular media item can be found by referencing similar media items. The hierarchical tree has nodes that are the media items and each node further includes a prominence level that indicates a relative popularity of the media item. Systems and methods described herein allow a user to edit or modify the hierarchical tree by changing a position of a media item in the hierarchical tree or by changing a prominence level of the media item. If the edit or modification affects the integrity of the hierarchical tree, the hierarchical tree is automatically further modified to preserve the integrity while reflecting the edit or modification made by the user.

Abstract: Users collect digital media items such as songs, images, and videos into media libraries. Over time, the user can collect a very large number of media items making organization and use of the media library difficult and time-consuming. The systems and methods described herein alleviate this task by collecting metadata about the media items from multiple sources, determining a similarity between the media items, and clustering the media items with like media items. The systems and methods described herein can position the media items relative to one another in a layout based on their respective similarity. Feedback from the user and from other users can be added to the metadata and used to update the layout of the media items.