Google Inc.

Neha Pattan

Jennifer W Lin

Uday Ramakrishna Naik

Venu Vemula

Anna Berenberg

Prajakta Joshi

Mike Ying

Venkat Subbaiah Naidu Kotla

Ines Envid

Ines Clara Envid Lazaro

Grouping virtualized computing instances in cloud environments can be achieved utilizing groups of network endpoints, such as hardware devices, virtualized computing instances, etc. The network endpoint group (NEG) provides a logical grouping for providers of backend services that may be arranged on the network endpoints, and may be organized based on the backend service to be provided by the computing environments that operate as network endpoints. For example, the NEGs may be implemented for load balancing applications. The network endpoint groups, and the network endpoints included therein, may be managed using a framework of tools, libraries and application programming interfaces.

System and method for deploying, scaling and managing network endpoint groups in cloud computing environments

Methods and systems are provided for determining the intent of a recommendation made by a user of a mobile application where the application includes a plurality of separable components, any one or more of which the recommendation can apply to. An application in which a user recommendation control is provided for presentation to a user also includes a tag indicating how a recommendation of the application should be interpreted with respect to the components included therein. The tag can be set by the application developer and can be in the form of text (e.g., a keyword or term) or a uniform resource locator (URL). Where a tag references multiple components of an application, a recommending user can be presented with a recommendation intent query. The recommendation intent query allows a user to designate one or more components of the application to which the user's recommendation should be attributed.

Determining intent of a recommendation on a mobile application

Methods and systems are provided for allowing users to recommend advertisements displayed in a third-party application running on a user device while not granting the third-party application privileges to send such recommendations on behalf of the user. A social network application installed on the user device, and separate from the third-party application, acts as a proxy for advertisement recommendation requests (e.g., indications that a user wishes to recommend an advertisement displayed), and a user is required to confirm all such recommendation actions. In this manner, a third-party application (e.g., a 'malicious third-party application) cannot send advertisement recommendation requests, and/or requests to undo such recommendations, on its own as if it were the user.

System and method for sharing content on third-party mobile applications

Apparatus and method for providing unique device identification values for a network accessible device. In accordance with some embodiments, a unique device identifier value is generated in response to a data exchange operation with a network accessible device. The identifier value is subsequently transmitted by the device as a unique device identifier value in conjunction with the transmitting of a request for a subsequent data exchange operation with the device.

Single use identifier values for network accessible devices

Methods and systems are provided for allowing a user to categorize, organize, and/or visualize content recommendations made by the user. Various interactive controls are made available to a user who recommends an item of content, where the controls are designed to allow the user to assign one or more attributes (e.g., characteristics, categories, labels, properties, etc.) to the recommendation. A user can also organize content recommendations into one or more categories that can be customized by the user according to subject-matter, content format, recommendation strength, and the like. The user is also provided with the ability to view his or her content recommendations arranged in various graphical representations.

Allowing users to categorize and visualize content recommendations

Methods and systems are provided for presenting a user with a recommendation intent query in response to the user indicating that he or she recommends content. The recommendation intent query allows a user to designate (e.g., select, indicate, identify, choose, etc.) one or more components, subjects, characteristics, properties, etc., of the content to which the user's recommendation should be attributed. Therefore, the user's intent with regard to the recommendation can be determined, and a more detailed social annotation about the recommendation can be provided to other users in a social network. The recommendation intent query is in the form of a user interface containing a list of components, subjects, and characteristics of the recommended content, one or more of which may be designated by the user as being the intended target(s) of his or her recommendation.

Determining intent of a recommendation on a URL of a web page or advertisement

Methods, apparatuses, and computer-readable media for serving annotations are disclosed. When a contact of a user recommends an ad, the score of the ad may be boosted in an ad auction. The amount of boosting depends on contact affinity. Contacts with greater contact affinity may be more influential, and ads that are recommended by such contacts may have a higher click-through rate. The greater the affinity between the user and contact, the greater the boost to the ad score. Affinity may be measured by a weight value, which is determined by, for example, social network interactions, e-mail/instant messaging communications, and phone logs and contact lists.

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Mountain View, CA, United States of America

Neha Pattan