System and method to determine the validity of an interaction on a network
First Claim
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1. A computer-implemented method of identifying a possible illegitimate interaction of a presumed user on a network, the method comprising:
- generating by the user an interaction on network;
collecting data from the interaction, the data including aggregate measure data and unique feature data;
applying a predictive model to the aggregate measure data and the unique feature data to result in a risk value of a click interaction on the Internet, wherein the predictive model is built based on previously collected data, the previously collected data being collected from previous interactions and including previous aggregate measure data and previous unique feature data from the previous interactions;
determining a validity of the interaction based on the risk value;
saving the risk value in a database; and
charging an advertiser in accordance with the generated interaction on the network and based on the determined validity of the interaction.
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Abstract
The methods and systems of the invention utilize limited data to yield information about the validity of any given interaction with a website. Once validity information is available, an operator can determine whether or not to continue offering interactions to a given user. The determination could also relate to whether to report website interaction statistics based on undesired interactions, how to handle billing or payment for such undesired interactions, and what type of content to send to users who are interacting with the website in an undesirable manner.
61 Citations
24 Claims
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1. A computer-implemented method of identifying a possible illegitimate interaction of a presumed user on a network, the method comprising:
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generating by the user an interaction on network; collecting data from the interaction, the data including aggregate measure data and unique feature data; applying a predictive model to the aggregate measure data and the unique feature data to result in a risk value of a click interaction on the Internet, wherein the predictive model is built based on previously collected data, the previously collected data being collected from previous interactions and including previous aggregate measure data and previous unique feature data from the previous interactions; determining a validity of the interaction based on the risk value; saving the risk value in a database; and charging an advertiser in accordance with the generated interaction on the network and based on the determined validity of the interaction. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A computer-implemented method of rating a user interaction on a network, the method comprising:
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generating by the user an interaction on network; collecting data from the interaction, the data including aggregate measure data and unique feature data; applying a predictive model to the aggregate measure data and the unique feature data to result in a risk value for a click interaction on the Internet, wherein the predictive model is built based on previously collected data, the previously collected data being collected from previous interactions and including previous aggregate measure data and previous unique feature data from the previous interactions; rating the interaction based on the risk value; saving the risk value in a database; and charging an advertiser in accordance with the generated interaction on the network and based on the rating of the interaction. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A system for detecting a possibly fraudulent interaction in a pay-for-placement search engine, the system comprising:
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at least one interaction with the pay-for-placement search engine being generated by a user; a first processor for collecting aggregate measure data and unique feature data about the interaction; and a second processor for applying a predictive model to the aggregate measure data and unique feature data to result in a risk value for a click interaction on the Internet, wherein the predictive model is built based on previously collected data, the previously collected data being collected from previous interactions and including previous aggregate measure data and previous unique feature data from the previous interactions, wherein the a legitimacy of the interaction is determined based on the risk value, and wherein an advertiser is charged in accordance with the at least one interaction with the search engine and based on the risk value for the interaction. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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Specification