Yahoo! Inc.

Pandora Media, Inc.

Huawei Technologies Co., Limited

Todd Beaupre

Jeffrey R Boulter

Christopher T Szeto

Jagdish Chand

Pierre Schiro

Vinod Pandurang Dhomse

Malcolm G Slaney

Deepak Agarwal

Scott Roy

Wei Chu

Raghu Ramakrishnan

Seung-Taek Park

Eric M Gottschalk

David E Brown

James Decarlo

John-Paul Veilleux

A method and computer readable medium for exploring similar users and items of a media service includes generating a user interface. The user interface displays a user selectable indicia representing a similar member function for allowing a user to search a media service for at least one other user. The one other user has a degree of similarity with respect to the searching user. Another method includes facilitating the search of such a similar user within a media service.

Method and system for exploring similarities

A method and computer readable medium for exploring similar users and items of a media service. In one aspect, a user can explore for similar users iteratively. In one aspect, a user interface is generated that displays a user selectable indicia representing a similar member function for allowing a user to search a media service for at least one other user which has a degree of similarity with respect to the searching user. In another aspect, a method facilitates the search of such a similar user within a media service.

Data streams are generally selected according to user preferences and transmitted to the user in general alignment with expressed preferences of the user. Such data streams may be music, including music videos. Users may indicate their general or specific preferences with regards to song, artists, or albums. Any other aspects or factors that might affect the user's preferences can be taken into account. A playlist is created that combines all of these factors. The playlist then serves as the basis for feeding the data streams to the user. Each user is able to express his or her own preferences and receive music corresponding to those preferences on an on-going basis.

Internet radio and broadcast via crowdsourcing apparatus and system

Internet radio and broadcast apparatus and system with music information and purchasing

Internet radio and broadcast method with music purchasing

Internet radio and broadcast method with artist portal

Internet radio and broadcast method personalized by genre

Internet radio and broadcast method personalized by ratings feedback

Internet radio and broadcast method

Internet radio and broadcast method with discovery settings

Internet radio and broadcast method with selectable explicit lyrics filtering

Internet radio and broadcast method personalized by DJ

A set of item-item affinities for a plurality of items is determined based on collaborative-filtering techniques. A set of an item's nearest neighbor items based on the set of item-item affinities is determined. A set of user feature-item affinities for the plurality of items and a set of user features is determined based on least squared regression. A set of a user feature's nearest neighbor items is determined based in part on the set of user feature-item affinities. Compatible affinity weights for nearest neighbor items of each item and each user feature are determined. Based on user features of a user and items a user has consumed, a set of nearest neighbor items are identified as a set of candidate items, and affinity scores of candidate items are determined. Based on the affinity scores, a candidate item from the set of candidate items is recommended to the user.

Determining user preference of items based on user ratings and user features

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Los Angeles, CA, United States of America

Todd Beaupre