System and method for a data driven meta-auction mechanism for sponsored search
First Claim
1. A method implemented in a computer system having at least one processor, storage, and a communication platform, comprising:
- performing by the at least one processor the steps of;
accessing an adaptive learning algorithm to maximize an objective function for online keyword auctions of one or more bidded terms each comprising one or more keywords, wherein the adaptive learning algorithm comprises one or more learning parameters, and each online keyword auction comprises one or more auction parameters; and
determining optimal values of the one or more learning parameters of the adaptive learning algorithm, includingchanging values of the one or more learning parameters of the adaptive learning algorithm using a stochastic optimization method,simulating one or more online keyword auctions,calculating values of the objective function based on results of the one or more simulated online keyword auctions,determining the optimal values of the one or more learning parameters that maximize the objective function, andstoring the determined optimal values of the one or more learning parameters of the adaptive learning algorithm in a data store.
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Abstract
Apparatuses, methods, and systems directed to deriving optimal parameters of a learning algorithm to maximize an objective function of online keyword auctions for bidded terms. Some embodiments of the invention simulate online keyword auctions based on historical data for the bidded terms, wherein the parameters of the simulated auctions such as market reserve prices of the bidded terms are determined by an adaptive learning algorithm. The values of the parameters of the learning algorithm are optimized by a stochastic optimization method to maximize an objective function for the auctions of the bidded terms.
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Citations
9 Claims
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1. A method implemented in a computer system having at least one processor, storage, and a communication platform, comprising:
performing by the at least one processor the steps of; accessing an adaptive learning algorithm to maximize an objective function for online keyword auctions of one or more bidded terms each comprising one or more keywords, wherein the adaptive learning algorithm comprises one or more learning parameters, and each online keyword auction comprises one or more auction parameters; and determining optimal values of the one or more learning parameters of the adaptive learning algorithm, including changing values of the one or more learning parameters of the adaptive learning algorithm using a stochastic optimization method, simulating one or more online keyword auctions, calculating values of the objective function based on results of the one or more simulated online keyword auctions, determining the optimal values of the one or more learning parameters that maximize the objective function, and storing the determined optimal values of the one or more learning parameters of the adaptive learning algorithm in a data store. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. An apparatus, comprising:
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at least one processor; and a memory configured to store logic that, when executed by the at least on processor, causes the at least one processor to perform the steps of; accessing access an adaptive learning algorithm to maximize an objective function for online keyword auctions of one or more bidded terms each comprising one or more keywords, wherein the adaptive learning algorithm comprises one or more learning parameters, and the online keyword auctions comprise one or more auction parameters; and determining optimal values of the one or more learning parameters of the adaptive learning algorithm, including changing values of the one or more learning parameters of the adaptive learning algorithm using a stochastic optimization method, simulating one or more online keyword auctions, calculating values of the objective function based on results of the one or more simulated online keyword auctions, and determining the optimal values of the one or more learning parameters that maximize the objective function.
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Specification