Verizon Patent and Licensing Inc.

Oath Inc.

Verizon Media Inc.

Teppo Veikko Salonen

Eric Theodore Bax

Lisa Giaffo

John Donald

Kimberly Williams

Liang Wang

Angus Xianen Qiu

Chun Han

One or more computing devices, systems, and/or methods for executing feedback actions based upon vehicle practices are provided. For example, sensor data is collected from sensors configured to collect sensor data associated with vehicles. The sensor data is synthesized to attribute sensor data to vehicle motion of the vehicle in relation to other objects. The vehicle motion is synthesized to determine driving actions of the vehicle, such as switching lanes, making a left hand turn, running a red light, etc. Vehicle practices of the vehicle are defined based upon the driving actions, such as a vehicle practice of a driver running red lights. A feedback action is executed to either reward the vehicle practices or incentivize a change in the vehicle practices.

Systems and methods for executing feedback actions based upon vehicle practices

One or more computing devices, systems, and/or methods for transmitting response content items to devices are presented. For example, a graphical user interface may be controlled to display an interface. The targeting interface may comprise a selectable input. The selectable input may correspond to a content item. A request for a targeted response to the content item may be received via the interface. The request may comprise a response content item and a selection of the selectable input. A plurality of assignments of the content item to a plurality of users may be determined. The response content item may be transmitted to a plurality of devices. Each device of the plurality of devices may be associated with a user of the plurality of users.

Transmitting response content items

The present teaching generally relates to detecting fraudulent networks. First data associated with a plurality of entities may be obtained, and a representation characterizing similarities among the plurality may be generated. Based on the representation, at least one entity cluster may be identified as corresponding to a candidate fraud network. A score associated with each of the at least one entity cluster may be determined, where the score indicates a likelihood that a corresponding entity cluster represents a fraud network, and at least some of the at least one entity cluster may be identified as a fraud network based on the score.

Method and system for identifying fraudulent publisher networks

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Temple City, CA, United States of America

Teppo Veikko Salonen