Systems and methods for user propensity classification and online auction design
First Claim
Patent Images
1. A server computing device, comprising:
- a network interface configured to;
receive a detection message from a publisher server, the detection message including user activity information on a webpage operated by the publisher server;
receive a bid request from an advertiser server; and
receive dimensional information; and
a processor in communication with the network interface, the processor configured to;
generate a sample based on at least one of the detection message, the bid request, or the dimensional information;
run the sample through a set of cascading classifier models, wherein the running the sample through the set of cascading classifier models comprises;
inputting the sample to a first classifier model of the set of cascading classifier models;
determining whether the sample is associated with a value exceeding a predetermined revenue threshold of the first classifier model; and
responsive to determining that the sample is associated with a value exceeding the predetermined revenue threshold, inputting the sample to a second classifier model of the set of cascading classifier models;
predict a floor price value based on the sample running through the set of cascading classifier models; and
implement an online bid auction based on the floor price value.
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Abstract
Systems, devices, and methods are disclosed for predicting a dynamic floor price for increasing cleared revenue cleared after a winning bid is determined in an online bid auction. The dynamic floor price is predicted from a cascading classifier strategy implemented through a series of cascading machine learning based classifier models that have been trained.
9 Citations
20 Claims
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1. A server computing device, comprising:
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a network interface configured to; receive a detection message from a publisher server, the detection message including user activity information on a webpage operated by the publisher server; receive a bid request from an advertiser server; and receive dimensional information; and a processor in communication with the network interface, the processor configured to; generate a sample based on at least one of the detection message, the bid request, or the dimensional information; run the sample through a set of cascading classifier models, wherein the running the sample through the set of cascading classifier models comprises; inputting the sample to a first classifier model of the set of cascading classifier models; determining whether the sample is associated with a value exceeding a predetermined revenue threshold of the first classifier model; and responsive to determining that the sample is associated with a value exceeding the predetermined revenue threshold, inputting the sample to a second classifier model of the set of cascading classifier models; predict a floor price value based on the sample running through the set of cascading classifier models; and implement an online bid auction based on the floor price value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for predicting a floor price, comprising:
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receiving, by a processor, a detection message sent from a publisher server, the detection message including user activity information on a webpage operated by the publisher server; receiving, by the processor, a bid request sent from an advertiser server; receiving, by the processor, dimensional information; generating, by the processor, a sample based on at least one of the detection message, the bid request, or the dimensional information; running, by the processor, the sample through a set of cascading classifier models, wherein the running the sample through the set of cascading classifier models comprises; inputting the sample to a first classifier model of the set of cascading classifier models; determining whether the sample is associated with a value exceeding a predetermined revenue threshold of the first classifier model; and responsive to determining that the sample is associated with a value exceeding the predetermined revenue threshold, inputting the sample to a second classifier model of the set of cascading classifier models; predicting, by the processor, a floor price value based on the sample running through the set of cascading classifier models; and implementing an online bid auction based on the floor price value. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A non-transitory computer readable medium storing a set of processor executable instructions that, when executed by a processor, cause the processor to:
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receive a detection message sent from a publisher server, the detection message including user activity information on a webpage operated by the publisher server; receive a bid request sent from an advertiser server; receive dimensional information; generate a sample based on at least one of the detection message, the bid request, or the dimensional information; run the sample through a set of cascading classifier models, wherein the running the sample through the set of cascading classifier models comprises; inputting the sample to a first classifier model of the set of cascading classifier models; determining whether the sample is associated with a value exceeding a threshold of the first classifier model; and responsive to determining that the sample is associated with a value exceeding the threshold, inputting the sample to a second classifier model of the set of cascading classifier models; predict a floor price value based on the sample running through the set of cascading classifier models; and implement an online bid auction based on the floor price value. - View Dependent Claims (17, 18, 19, 20)
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Specification