Google Inc.

Steve Lawrence

Jeffrey Adgate Dean

Simon Tong

Paul Haahr

Karl Pfleger

Monika Hildegard Henzinger

Olcan Sercinoglu

Anurag Acharya

Matt Cutts

Monika Henzinger

David P Marmaros

Krishna Asur Bharat

Mehran Sahami

Amit Singhal

Urs Hoelzle

Nikhil Bhatla

Tomas Gunnarsson

Satish Sampath

A system determines an extent to which advertisements are presented or updated within a document, a quality of an advertiser associated with an advertisement provided within the document, whether an advertisement in the document relates to an advertising document that has more than a threshold amount of traffic, and/or an extent to which an advertisement provided within the document generates user traffic to an advertising document related to the advertisement. The system generates a score for the document based, at least in part, on the extent to which advertisements are presented or updated, the quality of the advertiser associated with the advertisement, whether the advertisement relates to an advertising document that has more than the threshold amount of traffic, and/or the extent to which the advertisement generates user traffic to the advertising document. The system ranks the document with regard to at least one other document based on the score.

Document scoring based on traffic associated with a document

A user interface application, such as a sidebar application or web page, receives content from a set of plug-in modules. The user interface handles the display of the content and manages any user interaction with the content, thus abstracting these features from the plug-in modules. The plug-in modules may thus be device-independent and possibly used to display the same or corresponding content in other interfaces and/or other devices. One or more of the plug-in modules may also be designed to obtain and populate their content automatically based on user activity, including web browsing or interactions with documents on the local system.

Software architecture for displaying information content from plug-in modules in a user interface

A system may obtain search results associated with a search performed using a search query. The system may modify the search results, if necessary, based at least in part on information associated with prior document accesses by a user and present the modified search results to the user. The modification of the search results might including adding, deleting, and/or reordering items in the search results. One or more advertisements relevant to the search query may also be presented to the user along with the modified search results.

Systems and methods for providing searchable prior history

A system may determine an extent to which a document is selected when the document is included in a set of search results, generate a score for the document based, at least in part, on the extent to which the document is selected when the document is included in a set of search results; and rank the document with regard to at least one other document based, at least in part, on the score.

Document scoring based on query analysis

A system may determine a measure of how a content of a document changes over time, generate a score for the document based, at least in part, on the measure of how the content of the document changes over time, 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 content update

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 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

Ads are scored using, at least, user information and information associated with a user request, such as a search query or a document request. The scores may be used in determining whether to serve ads, how to serve ads, to order ads, to filter ads, etc. Items of user information, request-associated information, and/or ad information can be weighted based on previous uses of such information in the serving of ads and the performance of those served ads.

Serving advertisements using user request information and user information

A system determines an extent to which advertisements are presented or updated within a document, a quality of an advertiser associated with an advertisement provided within the document, whether an advertisement in the document relates to an advertising document that has more than a threshold amount of traffic, and/or an extent to which an advertisement provided within the document generates user traffic to an advertising document related to the advertisement. The system generates a score for the document based, at least in part, on the extent to which advertisements are presented or updated within the document, the quality of the advertiser associated with the advertisement provided within the document, whether the advertisement relates to an advertising document that has more than the threshold amount of traffic, and/or the extent to which the advertisement generates user traffic to the advertising document. The system ranks the document with regard to at least one other document based, at least in part, on the score.

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Mountain View, CA, United States of America

Steve Lawrence