Google Inc.

Daniel Wesley Dulitz

Sanjay Ghemawat

Jeffrey Adgate Dean

Alexandre A Verstak

Seth J Golub

Andrew Stephen Tomkins

Andre Rohe

Emily Kay Moxley

Justin Lewis Kosslyn

Josh T Wills

Evan Mallory Gilbert

Manish P Gupta

Brett Rolston Lider

Anurag Acharya

Jonathan Terleski

Rajas Moonka

Jessica Nicola Staddon

Vivek Paul Gundotra

Pavani Naishadh Diwanji

David Glazer

David Mark Byttow

Keith H Randall

Steve Okamoto

Karen Padham Taylor

Bwolen Po-Jen Yang

Chade-Meng Tan

Moti Yung

Susan Wojcicki

Garry Boyer

Aron Giles

Matthew Allen Gundersen

Vic Gundotra

A system and machine-implemented method for processing a social endorsement for an item. Structured data for a first item is received in association with a first webpage, the structured data for the first item defining properties of the first item that are specific to the first item. An indication of a social endorsement for the first item is received in association with the first webpage. In response to receiving the indication of the social endorsement, an item element corresponding to the first item is identified within a data structure. The data structure stores plural item elements, each item element including a description of the item and social endorsement information associated with the item. The social endorsement information associated with the identified item element is updated within the data structure, based on the received indication of the social endorsement for the first item.

Processing a social endorsement for an item

Systems and methods are provided that, in response to obtaining an email to a recipient from a sender, and in accordance with a determination that an indirect relationship exists between the sender and the recipient, determine a spam probability of the email by evaluating statistical information regarding the historical electronic interactions associated with the sender. In this way, the email is classified according to the identified spam probability.

System for reclassification of electronic messages in a spam filtering system

A system and method for generating a channel includes a channel engine that retrieves candidate content items based on a topic from heterogeneous data sources. The channel engine generates a stream of content with selected content items and populates the stream of content for the channel and providing the stream of content to users associated with the channel. In response to receiving feedback, the channel engine modifies the at least one topic based at least in part on the feedback. The scoring engine generates a second stream of content from the first stream of content that is personalized for the first user based at least in part on a model. Other users can subscribe to the second stream.

Stream of content for a channel

In one aspect, a system for presenting a share box with content information in response to an endorsement includes an endorsement sharing module that is responsive to user input and creates a sharing box having content derived from the user context and input request. The endorsement sharing module receives a user request to share information. In response, this endorsement sharing module determines the context of the user, retrieves content based on the context, filters the content based on publisher information, personalizes the share box content, and adds the content to a share box. The endorsement sharing module also adds one or more actions to the share box after which the share box is provided for display to the user.

Share box for endorsements

A system and method for generating privacy-enhanced aggregate statistics within a social network system is provided. Data is collected and processed to gather information to generate the aggregate statistics. A threshold is assigned. The threshold includes a criterion used in making a determination on what aggregate statistic will be generated. In some embodiments, the threshold is a numerical value. In some embodiments, the numerical value, or quantitative data is then translated into qualitative descriptors. In some embodiments, noise is then added to randomize the assigned threshold. In other embodiments, noise is added to the collected data. In some embodiments, checks to guard against attacks from adversarial users are performed. Examples of indications of adversarial behavior include, but are not limited to, manipulation of profiles, continuous manipulation of affinity groups, and manipulation of preferences for one or more users. The threshold is applied and aggregate statistics are generated.

System and method for generating privacy-enhanced aggregate statistics

Systems and methods for indexing a representative document from a set of duplicate documents are disclosed. Disclosed systems and methods comprise selecting a first document in a plurality of documents on the basis that the first document is associated with a query independent score. Each respective document in the plurality of documents has a fingerprint that indicates that the respective document has substantially identical content to every other document in the plurality of documents. Disclosed systems and methods further comprise indexing, in accordance with the query independent score, the first document thereby producing an indexed first document. With respect to the plurality of documents, only the indexed first document is included in a document index.

Representative document selection for a set of duplicate documents

A method for indicating probability of spam for email comprises tracking network traffic characteristics for the email, and comparing the tracked characteristics for the email to characteristics for email from trusted or known spam sources.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for facilitating online conversation. In one aspect, a method includes determining that a user has submitted a question to be viewed by trusted participants of an online conversation, wherein the trusted participants include the user, one or more advertisers and one or more social network friends of the user, obtaining a reply to the question from one of the trusted participants, and providing the reply to the trusted participants.

Method of answering questions by trusted participants

Trusted participants of social network providing answers to questions through on-line conversations

Duplicate documents are detected in a web crawler system. Upon receiving a newly crawled document, a set of documents, if any, sharing the same content as the newly crawled document is identified. Information identifying the newly crawled document and the selected set of documents is merged into information identifying a new set of documents. Duplicate documents are included and excluded from the new set of documents based on a query independent metric for each such document. A single representative document for the new set of documents is identified in accordance with a set of predefined conditions.

Representative document selection for sets of duplicate documents in a web crawler system

A query including one or more keywords is received. An advertisement associated with the one or more keywords is identified, and display data for displaying the advertisement is generated and a determination is made as to whether the advertisement is associated with a video. Video selection data is generated for displaying the video proximate to the advertisement if the advertisement is determined to be associated with the video, and the display data and the video selection data are provided.

Video advertisements

Duplicate document detection in a web crawler system

Growing community of inventors

Mountain View, CA, United States of America

Daniel Wesley Dulitz