Apple Inc.

Strands, Inc.

Marc Torrens

Francisco J Martin

Jim Shur

Pere Ferrera

Rick Hangartner

Craig Rowley

Guillermo Caudevilla-Laliena

Josep-Lluis Arcos

David Del Ser Bartolome

Patrick Hertzog

Systems and methods are disclosed for identifying a new set of media items in response to an input set (or 'query set') of media items and knowledge base metrics. The system uses a knowledge base consisting of a collection of mediasets. Various metrics among media items are considered by analyzing how the media items are grouped to form the mediasets in the knowledge base. Such association or 'similarity' metrics are preferably stored in a matrix form that allows the system to efficiently identify a new set of media items that complements the input set of media items.

Recommender system for identifying a new set of media items responsive to an input set of media items and knowledge base metrics

Disclosed are various embodiments of systems and methods for generating composite mediasets from mediasets, each comprising media items, associated with a plurality of users. In some embodiments, individual and/or group recommendations are provided for creating a group playlist by aggregating user taste data for a plurality of users in a group. In other embodiments, systems and methods are provided which allow for sharing and playing of a group playlist by users in a group, each of which has a media playback device. In still other embodiments, systems and methods are provided for dynamically building a composite playlist that may be updated as users enter and/or leave the group. One example of an interactive entertainment application also is described for use at a venue to entertain live guests with music selections that are dynamically influenced by the guests' individual tastes.

Dynamic interactive entertainment venue

Disclosed are embodiments of systems and methods for recommending relevant users to other users in a user community. In one implementation of such a method, two different sets of data are considered: a) music (or other items) that users have been listening to (or otherwise engaging), and b) music (or other items) recommendations that users have been given. In some embodiments, pre-computation methods allow the system to efficiently compare item sets and recommended item sets among the users in the community. Such comparisons may also comprise metrics that the system can use to figure out which users should be recommended for a given target user.

User to user recommender

Disclosed are various embodiments of systems and methods for generating composite mediasets from mediasets, each comprising media items, associated with a plurality of users. In some embodiments, individual and/or group recommendations are provided for creating a group playlist by aggregating user taste data for a plurality of users in a group. In other embodiments, systems and methods are provided which allow for sharing and playing of a group playlist by users in a group, each of which has a media playback device. Each media item, such as a song, is played from one of the individual user devices for the benefit of all users in the vicinity at the time. Music thus can be 'shared' without transferring files potentially in violation of copyrights.

Mediaset generation system

A system and method to navigate through a media item catalog and generate recommendations using behavioral metrics such as correlation metrics (FIGS.) from a knowledge base () of mediasets (FIG.-). One implementation uses a knowledge base comprising a collection of mediasets such as groupings of selected video items. Various metrics (Metric-Metric m) among media items (m. . . ) are considered by analyzing how the media items are grouped to form the sets in the knowledge base (). Such metrics preferably are stored in a matrix () that allows the system to dynamically build appropriate navigation lists (FIG.) from media items that a user selects (FIG.).

System for browsing through a music catalog using correlation metrics of a knowledge base of mediasets

Visualizing and exploring a music library using metadata, such as genre, sub-genre, artist, and year, is provided. Geometric shapes, such as disks or rectangles, may be divided into sectors representing genre and each sector may be further divided into sub-sectors representing artists associated with each genre. The sector's relative size generally reflects the importance of the corresponding genre within the library. Likewise, the sub-sector's relative size generally reflects the importance of the corresponding artist within the genre which may be determined by the number of media items of the artist. Marks representing each media item may be arranged and displayed within the geometric shape to reflect the mark's corresponding genre, artist, and year. In addition, each mark may reflect an attribute, such as playcount, of the media item and each sector may reflect the mean value of an attribute of all media items within the sector.

Methods and apparatus for visualizing a media library

A system and method to navigate through a media item catalog and generate recommendations using behavioral metrics such as correlation metrics (FIGS.) from a knowledge base () of mediasets (FIG.-). One implementation uses a knowledge base comprising a collection of mediasets. Various metrics (Metric-Metric m) among media items (m. . . ) are considered by analyzing how the media items are grouped to form the sets in the knowledge base (). Such metrics preferably are stored in a matrix () that allows the system to dynamically build appropriate navigation lists (FIG.) from media items that a user selects (FIG.).

A system to navigate through a media item catalog using correlation metrics (FIGS.) from a knowledge base () of mediasets (FIG.-). The system uses a knowledge base consisting of a collection of mediasets. Various metrics (Metric-Metric m) among media items (m. . . ) are considered by analyzing how the media items are grouped to form the sets in the knowledge base (). Such metrics preferably are stored in a matrix () that allows the system to dynamically build appropriate navigation lists (FIG.) from media items that a user selects (FIG.).

Growing community of inventors

Corvallis, OR, United States of America

Marc Torrens