Click rate estimation system and method based on field-programmable gate array

Abstract

The invention provides a click rate estimation system and method based on a field-programmable gate array. The click rate estimation system based on the field-programmable gate array comprises a datainterface module, a model parameter storage module, a calculation control module, a factorization machine calculation module and a neural network calculation module, wherein the data interface moduleis used for acquiring model parameters, acquiring to-be-estimated data and outputting a click rate estimation result; the model parameter storage module is used for storing model parameters; the calculation control module is used for obtaining to-be-estimated data from the data interface module and obtaining model parameters from the model parameter storage module; the factorization machine calculation module is used for calculating a factorization machine expression of the to-be-estimated data; the neural network calculation module is used for calculating a neural network forward propagationresult of the to-be-estimated data; and the calculation control module is also used for obtaining a click rate estimation result. According to the technical scheme of the embodiment of the invention,the calculation delay of click rate estimation is reduced, and the calculation speed is improved.

Description

technical field [0001] The present application relates to the technical field of Internet advertising, and in particular to a field programmable gate array-based system and method for predicting click-through rates. Background technique [0002] With the rapid development of the Internet, Internet advertising also rises. Compared with traditional advertising, Internet advertising is one of the important parts of implementing modern marketing media strategy. Advertisement click-through rate prediction (PCTR, Predict Click-Through Rate) is the core issue in the field of Internet advertising. Advertisement click-through rate estimation is to predict the probability that a specific user will click on a push advertisement. [0003] At present, the commonly used advertising click-through rate estimation methods need to occupy a large amount of computer memory resources and computing time, and, for some large-scale websites or databases, with tens of millions of user characteristic...

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Problems solved by technology

[0003] At present, the commonly used advertising click-through rate estimation methods need to occupy a large amount of computer memory resources and computing time, and, for some large-scale websites or databases, which have tens of millions of user characteristic data, it is necessary to use large-scale user characteristic data based on Estimate the click-through rate of advertisements, and realize the prediction algorithm of click-through rates of advertisements through the central processing unit, which has the problems of high calculation delay and slow calculation speed

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