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Systems and methods for establishing and utilizing a hierarchical Bayesian framework for ad click through rate prediction
Systems and methods for establishing and utilizing a hierarchical Bayesian framework for ad click through rate prediction
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机译：用于建立和利用分层贝叶斯框架进行广告点击率预测的系统和方法
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摘要
The present disclosure relates to a computer system configured establish and utilize a database for online ad realization prediction in an ad display platform associated with N parties, wherein N is a positive integral greater than 1. The computer system is configured obtain a party hierarchy for each of the N parties including a plurality of features of the party; select a target ad display event including N features, each of the N features corresponding to a node in a party hierarchy; obtain a prior probability reflecting an unconditional probability of ad realization occurrence at the target ad display event among all possible ad display events; for each of the N features: determine a marginal prior probability by decomposing components associated with the other N−1 features from the prior probability; determine a marginal posterior probability based on the marginal prior probability; and save the marginal posterior probability in the corresponding node of the party hierarchy.
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