Click fraud resistant learning of click through rate
First Claim
1. A system that facilitates online advertisement data predictions, comprising:
- a receiving component that receives at least one event data set relating to an online advertisement; and
a probability component that determines an occurrence value of a first event type from the obtained event data based on an occurrence value of a second event type from the obtained event data that is a conversion of the first event type and learns an expected event wait based on the first and second event type occurrence values.
2 Assignments
0 Petitions
Accused Products
Abstract
Click-based algorithms are leveraged to provide protection against fraudulent user clicks of online advertisements. This enables mitigation of short term losses due to the fraudulent clicks and also mitigates long term advantages caused by the fraud. The techniques employed utilize “expected click wait” instead of CTR to determine the likelihood that a future click will occur. An expected click wait is based on the number of events that occur before a certain number of clicks are obtained. The events can also include advertisement impressions and/or sale and the like. This flexibility allows for fraud detection of other systems by transforming the other systems to clock-tick fraud based systems. Averages, including weighted averages, can also be utilized with the systems and methods herein to facilitate in providing a fraud resistant estimate of the CTR.
-
Citations
20 Claims
-
1. A system that facilitates online advertisement data predictions, comprising:
-
a receiving component that receives at least one event data set relating to an online advertisement; and
a probability component that determines an occurrence value of a first event type from the obtained event data based on an occurrence value of a second event type from the obtained event data that is a conversion of the first event type and learns an expected event wait based on the first and second event type occurrence values. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A method for facilitating online advertisement data predictions, comprising:
-
receiving at least one event data set relating to an online advertisement; and
learning an expected wait of an event from the event data set via integration of the learning over a past fixed number of events. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17, 20)
-
-
18. A method of auctioning online advertisements, comprising:
-
employing an expected click wait to facilitate in determining a likelihood of a future click on an advertisement impression by a user; and
utilizing the likelihood to facilitate in determining a pricing structure to charge an advertiser for each future click of the advertisement impression. - View Dependent Claims (19)
-
Specification