Google Inc.

Nandini Kappiah

Andrew Granoff

Michael Yue Zhang

Orkut Buyukkokten

Madhukar N Thakur

Richard J Engelberg

Divya Shah

Dharmeshkumar Mokani

Jesse P Stollak

Bharadwaj Subramanian

Xavier Llora

Morgan Avery Conbere

Katherine Huang

Andrew Beckmann Sellergren

Oleg Chernyakhovskiy

Luis Alberto Rojas Marambio

Francesco Xavier Llora Fabrega

Sergio Marti

Jennifer Hope Carter

Guanggi Ye

Guangqi Ye

Karen Lees

Categorizing accounts based on associated images is described, including identifying information associated with an account associated with a user, the information includes an image associated with the user; producing data associated with the image; computing a threshold value associated with the account based at least on the data associated with the image, the threshold value is associated with a category of accounts; and performing an operation associated with the account based on the threshold value.

Categorizing accounts based on associated images

The present disclosure includes systems and methods for classifying user content (e.g., spam) within an online community by determining user specific signals and content specific signals, the systems and methods comprising: a user interface module configured to receive user content from the online community, a social signal processing module configured to determine signals from the user content, a user and content classifying module configured to classify user content and configured to compute a decision on the user content, a user content labeling module configured to label the user content, and an execution module configured to execute the decision.

Determining user content classifications within an online community

A system for protecting endorsement events against anomalous behaviors is disclosed. The system includes a data collecting module, an activity recording module, an aggregation module, a detection module and an action module. The data collecting module collects event data describing one or more endorsement events. The activity recording module records activity data associated with the one or more endorsement events. The aggregation module aggregates the activity data. The detection module detects, based at least in part on the aggregation of the activity data, one or more anomalies associated with the one or more endorsement events. The action module takes one or more protection actions responsive to the detection of the one or more anomalies. The present disclosure also includes a method for protecting endorsement events against anomalous behaviors.

Anomaly detection for online endorsement event

A method, system, and graphical user interface for personalized online sports team charts are disclosed. One aspect of the invention involves a graphical user interface on a computer that includes a graphic of an athletic playing field or a portion thereof, and a plurality of player positions on the athletic field. At least some of the player positions contain thumbnail images selected by a first user. The thumbnail images provide links to corresponding profiles in an online social network.

Method, system, and graphical user interface for personalized online sports team charts

Growing community of inventors

Los Gatos, CA, United States of America

Nandini Kappiah