Google Inc.

Matt Cutts

Simon Tong

Jeffrey Adgate Dean

Paul Haahr

Karl Pfleger

Steve Lawrence

Fritz Schneider

Niels Provos

Monika Henzinger

Adam Dingle

Sanjay Ghemawat

Anurag Acharya

Amit Singhal

Jun Wu

John Piscitello

Monika Hildegard Henzinger

Olcan Sercinoglu

Urs Hoelzle

A system may present information regarding a document and provide an option for removing the document. The system may also receive selection of the option and remove the document when the option is selected. The system may aggregate information regarding documents that have been removed by a group of users and assign scores to a set of documents based on the aggregated information.

Permitting users to remove documents

A system includes a data repository and a processing unit. The data repository stores data associated with a corpus of documents hosted on one or more servers. The processing unit analyzes data associated with a suspect document from the corpus of documents. The processing unit further assigns a score, based on the analyzed data, to the suspect document that indicates whether the suspect document is potentially fraudulent.

Systems and methods for detecting potential communications fraud

A system may determine a document inception date associated with a document, generate a score for the document based, at least in part, on the document inception date, and rank the document with regard to at least one other document based, at least in part, on the score.

Document scoring based on document inception date

A system processes user queries. The system may generate a list of query patterns of a first type. The system may also receive a user query and determine whether the received query is a query of the first type based at least in part on the list of query patterns.

Systems and methods for detecting commercial queries

A method may include receiving a document and an initial score for the document; determining that there has been a decrease in a rate or quantity of new links that point to the document over time; classifying the document as stale in response to the determining; decreasing the initial score for the document, resulting in an updated score; and ranking the document with regard to at least one other document based, at least in part, on the score.

Document scoring based on link-based criteria

A system detects hidden elements in a document that includes a group of elements. The system may identify each of the elements in the document and create a structural representation of the document. The structural representation may provide an interconnection of the group of elements in the document. The system may also determine whether one or more elements of the group of elements are hidden based at least in part on locations or other attributes or properties of the one or more elements in the structural representation.

Systems and methods for detecting hidden text and hidden links

A system identifies a document and obtains one or more types of history data associated with the document. The system may generate a score for the document based, at least in part, on the one or more types of history data.

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Mountain View, CA, United States of America

Matt Cutts