Google Inc.

Duncan John Curtis

Alexander Ruben Stacey McCarthy

Benjamin Frenkel

According to an implementation, an application distribution system may receive a search query from a user and generate indicators of a set of applications based on the search query. The system may determine an influence rating for an entity that provided social media posts associated with one of the applications. The system may determine a sentiment rating for the content of the posts and determine a reliability rating for the entity. The reliability rating may be based the number of posts and the number of the entity's social media relationships. The system may determine an application rating for the application based on the influence rating, the sentiment rating, and the reliability rating. The system may rank the application within a list of the set of applications based on the application rating and provide the list to the device associated with the user.

Social ranking for apps

A player model for a video game is generated based on inputs received from users who have played past versions of the game. The player model can be used to simulate user actions in a new version of the video game and make predictions about average user session length, average earnings per session, number of games played per day, etc. More than one player model may be generated for a game. Each player model for a game may represent one or more features, such as a user skill level, for a group of users.

Player model

Systems, device and techniques are disclosed for receiving content based on a subscription to channel by a user. An indication of a user subscription, by a user, may be received. The subscription may be for a channel associated with a channel manager for the channel. An indication of a content to be provided via the channel may be received from the channel manager for the channel. A determination may be made that the content value associated with the content is below an available user subscription value. The content may be automatically provided to the user, based on the determination and the content value may be deducted from the available subscription value.

Subscription model for trusted recommendation sources

Systems, device and techniques are disclosed for rating a multiplayer videogame active player based on the retention of one or more qualifying players after their interaction with the active player. An interaction event between an active player and a qualifying player may be detected and a retention value based on the qualifying player returning to the multiplayer videogame may be determined. The active player may be rated based at least on the retention value of the qualifying player.

Player rankings based on long term opponent activity

A video clip may be automatically generated from a gameplay recording based on an interest metric. The interest metric may be determined from a variety of sources, such as developer provided signals, platform-based signals, and reception signal. A machine learning technique may be applied to each of the signals individually and/or in aggregate (e.g., the interest metric) to ascertain a weighting scheme, for example, for each individual signal or the interest metric to improve the selection of portions of video from a gameplay recording.

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Castro Valley, CA, United States of America

Duncan John Curtis