Google Inc.

Khanh B Nguyen

Gregory J Friedman

Michael Alex Frumkin

Karthik Gopalratnam

Ralph U Gasser

Emily Kay Moxley

Dani Suleman

Hobart Sze

Vinod Anupam

Clarence Christopher Mysen

Alice S Tull

Myles A Sussman

Jennifer Liu Low

Edward A Baltz

Christopher M Roat

Advertisement quality measures (e.g., predicted click through rates) are modified in accordance with a user's preferences with respect to domains to which the advertisements relate.

User-based ad ranking

A bid for a content slot from a content provider is received. The bid includes a revenue-sharing bid. It is determined that the bid is a winning bid and content is presented from the content provider in the content slot. Presentation details are logged that include a time when the content was presented. At a later time, an indication is received of an action, the indication including an indication that the action is responsive to the content having been presented previously. Based on the action, the content provider is charged an appropriate amount based on the revenue sharing bid.

Managing revenue sharing bids

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, for providing content, comprising: identifying a social action that includes a preference designation for an object; determining a location of an individual user associated with the social action or a location associated with the object that is the subject of the preference designation; attributing the preference designation to both the location and to the individual user, where the attributed preference designation can be used to target further content to either the individual user or other users; and receiving a request for content that is related to the location and providing, responsive to the request, one or more content items based on the attributed preference designations.

Attributing preferences to locations for serving content

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining influence in a social community. In one aspect, a method includes identifying a user in a community; determining an influence score to be associated with the user in the community for a particular topic, including: determining a reach of one or more communications that relate to the particular topic that have been distributed from the user to other users in the community, and evaluating the reach as compared to the reach of one or more communications distributed from other users in the community for the particular topic; and storing the influence score in association with the user.

Determining influence in a social community

Methods and systems to modify the number and/or positioning of advertisements presented to a user based on that user's activity patterns (e.g., previous queries, query result selections, ad selections, etc.) and the order in which events constituting the activity patterns occurred. For example, the methods and systems can be based on a Markov model utilizing the user's activity patterns.

User-based advertisement positioning using markov models

Growing community of inventors

Cupertino, CA, United States of America

Khanh B Nguyen