Google Inc.

Kawaljit Gandhi

Chase Hensel

Julien Borel

Kamal P Nigam

Nitin Mangtani

Carl J Evankovich

Abdulrahman Salem

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving one or more search terms, providing the search terms as input to one or more user-specific indices, a user-specific index being generated based on an access privilege granted by a user to a data source, the data source including data that is specific to the user, generating search results based on the one or more search terms and the one or more user-specific indices, and transmitting the search results for display to a searching user.

Customized search engines

System, methods and articles of manufacture for tracking content across an Internet. An embodiment comprises receiving the content from a content source, wherein the content includes a unique content identifier, injecting the content into a content aggregation system, retrieving the unique content identifier from the content, analyzing the content based on the unique content identifier and data in the content aggregation system, and generating a report of the analyzed content.

Tracking content across the internet

Content providers can target individuals for receipt of selected content based, at least in part, on profiles associated with users. The associations between the users and the profiles are determined based on analysis of receipts for transactions completed by the users. These receipts contain information that is indicative of the individuals' spending habits. Electronic correspondence associated with the users is scanned to identify the receipts and information is extracted from the receipts for use in the analysis. The individuals can opt-in to receive content targeted to the profiles associated with their accounts without allowing the content providers to have direct access to their receipts or their identity. The individuals can also opt-out if they no longer want to receive targeted content.

Distributing content based on transaction information

A 'likeness factor' indicating users' endorsements of a product is disclosed. 'Likes,' &#x201c;dislikes,&#x201d; and other favorable or unfavorable user input for a product are collected from a website that displays the product and that logs such information. The collected information is made available on other websites displaying the product either directly or in the form of a likeness factor. The information can be aggregated from multiple websites and sources. A likeness factor for a manufacturer or other merchant is based on likeness factors for products of the manufacturer. Changes in likeness factor over time indicate a trend for products and manufacturers and can be used to predict product performance. Search results are filtered by likeness factor, and advertisements are presented based on likeness factor.

Aggregating product endorsement information

System, methods and computer program products for identifying a featured product based on product information submitted by retailers and manufacturers are described. In some implementations, a retailer and a manufacturer can supply product information to an ad serving system. Based on the product information supplied by the retailer and the manufacturer, a product matching the product can be identified. The matching product can then be presented on a content of the retailer that links to a product page of the matching product.

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San Francisco, CA, United States of America

Kawaljit Gandhi