Google Inc.

Luke Hiro Swartz

Kirill Buryak

Andrew Swerdlow

Cibu Chalissery Johny

Clement Roux

Gaurav Garg

Venky Ramachandran

Advay Mengle

Shreyas Doshi

Dani Suleman

Lakshmi Kumar Dabbiru

Poorva Hari Potdar

Angela Yu-Yun Yeung

Clément Roux

Michael Chu

Zhengrong Ji

Gadi Guy

Jeremy Aron-Dine

Vladimir Lanin

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium. A method includes: for each of a plurality of content items in an inventory of content items: identifying an entity associated with the content item and a plurality of page types for a vertical associated with a product or service described in the content item; locating a plurality of informational pages associated with the entity; classifying each informational page based on the page types; identifying queries associated with the entity, wherein a query is used as a selection criteria for delivering one or more content items associated with the entity; for each informational page of the plurality of informational pages determining relevant queries from the identified queries; and storing in a data structure an association between the content item, data associated with the relevant queries and associated informational pages.

Structured informational link annotations

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a query, receiving a set of social search results including one or more social media items that have been distributed through one or more computer-implemented services, each social media item being responsive to the query, providing a sub-set of social search results based on respective promotion scores provided in an auction, the sub-set of social search results including at least one social media item of the set of social search results, and providing the sub-set of social search results for display in a search results page, social media items of the sub-set of social search results being displayed based on respective promotion scores.

Promoting social media content in search

Systems and methods for measuring brand uplift in a computer networked environment are provided. A data processing system can assign a first set of device identifiers to an experimental arm and a second set of device identifiers to a control arm. Computing devices associated with the experimental arm receive third-party content items promoting a brand for which a brand uplift experiment is performed, while computing devices associated with the control arm do not receive third-party content items promoting the brand. At the end of the experiment, a brand uplift metric value is computed by analyzing search query logs of the computing devices. The brand uplift metric value is then provided to an advertiser for display.

Methods and systems for measuring brand uplift for search campaigns

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a system that includes a synthesis subsystem that automatically creates components for inclusion in a creative. The synthesis subsystem includes one or more modules that receive, as input, crawled content or metadata known or identified by the content serving system, and produce, as an output, a synthesized component for inclusion in a prospective creative. The system further includes an evaluation subsystem that evaluates quality of each of the synthesized components generated by the synthesis subsystem to determine measurable quality as against a baseline quality level. The system further includes a serving subsystem that receives queries and selects relevant content items responsive to the queries including, for a given content item, identification of one or more synthesized components generated by the synthesis subsystem depending on the evaluation of the respective synthesized components by the evaluation subsystem.

Automatic synthesis and evaluation of content

According to various embodiments of the disclosure techniques for generating outgoing messages are disclosed. The technique includes receiving a request to generate an outgoing message for a recipient and retrieving one or more recipient preferences of the recipient from a recipient preferences database. The one or more recipient preferences relate to customization of messages that are to be delivered to the recipient. The technique further includes retrieving a message template from a plurality of message templates stored in a message template database based on the request and the one or more recipient preferences. The technique also includes generating the outgoing message based on the retrieved message template and the one or more recipient preferences, and providing the outgoing message to the recipient.

Techniques for generating outgoing messages based on language, internationalization, and localization preferences of the recipient

Systems and methods for measuring brand uplift in a computer networked environment is provided. A data processing system can assign a first set of device identifiers to an experimental arm and a second set of device identifiers to a control arm. Computing devices associated with the experimental arm receive third-party content items promoting a brand for which a brand uplift experiment is performed, while computing devices associated with the control arm do not receive third-party content items promoting the brand. At the end of the experiment, a brand uplift metric value is computed by analyzing search query logs of the computing devices. The brand uplift metric value is then provided to an advertiser for display.

Techniques for determining one or more preferred languages for a user are provided. The preferred languages may be determined based upon a set of language indicators. The language indicators are analyzed using, for example, rules-based techniques, clustering, language classifiers, and the like, or combinations thereof. Language indicators can include or be derived from information about the user's behavior, location, preferences, social connections, or other data related to the user.

Language detection based upon a social graph

Cluster-based language detection

A computer-implemented technique includes determining, at a computing device including one or more processors, one or more scripts in which a user is capable of inputting text. The technique includes determining, at the computing device, whether at least one of the one or more scripts is a script having a right-to-left (RTL) writing directionality. The technique also includes automatically outputting, at the computing device: (i) a first user interface when at least one of the one or more scripts is a script having an RTL writing directionality, wherein the first user interface is configured to allow the user to adjust the writing directionality at the computing device, or (ii) a second user interface when none of the one or more scripts is a script having an RTL writing directionality, wherein the second user interface is not configured to allow the user to adjust the writing directionality at the computing device.

Techniques for providing a user interface having bi-directional writing tools

Techniques are shown for executing a web browser on a client computing device and requesting access to applications available from a hosting server over a network in communication with the client device. The web browser stores authorization credentials for accessing designated applications available from the hosting server in a lockbox. A message received at the web browser provides instructions to lock all designated applications by rendering at least partially blanked-out or partially obscured visual displays for the designated applications, with no viewing of, access to, or operation on selected data within the designated applications permitted, while the locked designated applications remain logged-in. This Abstract is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.

Browser session privacy lock

Language classifiers for language detection

Rules-based language detection

A process for a language selection using one or more language preferences is disclosed. Information for presenting a language preference selection control may be sent to a user. A language preference may be received from the user and stored to a server. A cookie, which includes an indication of the language preference, may be caused to be stored to a device of a user. The stored language preference may be accessed from the cookie responsive to a communication from the user. Responsive to whether the user has logged into an account, the language preference may be retrieved from either the server or from the cookie. The retrieved language preference may be compared with languages available in an application and a most preferred language for the application may be determined based upon the comparison. Information from the application may be provided to the user in the most preferred language.

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San Francisco, CA, United States of America

Luke Hiro Swartz