CORRECTION METHOD FOR ADVERTISEMENT CLICK-THROUGH RATE AND ADVERTISEMENT DELIVERY SERVER

摘要

The present invention relates to a technical field of computers, and discloses an advertisement click-through rate correction method and advertisement delivery server. The method comprises: using a logistic regression model to predict a click-through rate of each training sample to acquire a predicted value of the click-through rate of said training sample; querying an observation value of each training sample according to stored log data; calculating a correction value of the predicted value for each training sample according to the observation value of said training sample, so as to enable the correction value of the earlier predicted value of two adjacent predicted values to be smaller than or equal to the correction value of the latter predicted value. By correcting the predicted click-through rate corresponding to a training sample and acquiring the correction value of each predicted value, the present invention addresses a problem of related art during click-through rate prediction of a PCTR unit regarding to a difference between the predicted CTR and the real CTR resulting from a large amount of training data, such that the difference between the predicted click-through rate and the real click-through rate is reduced, and targeting of advertisement delivery to users is improved.