Patent ID: 11893071
Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Field: Audio-visual technology (Electrical engineering)
Classification: CPC G  H | IPC G  H

Claim 16:
17. The computer-readable storage medium according to claim 16, wherein the prediction model further comprises a wide component, a factorization machine (FM) component, and a deep neural networks (DNN) component, and the behavior preference information of the target object is a behavior preference feature vector; and
the performing feature extraction on the behavior preference information, the content feedback information, and the content feature information using the trained prediction model, and obtaining the predicted CTR that is outputted by the prediction model and at which the target object clicks the content that is to be recommended further comprises:
learning weight contributions of different feature fields in the object portrait information and the content feature information based on the wide component, and obtaining a feature weight vector;
performing feature extraction on the behavior preference feature vector and the dense feature vectors based on the FM component, and obtaining a low-order interaction feature vector corresponding to the target object;
performing feature extraction on the behavior preference feature vector and the dense feature vectors based on the DNN component, and obtaining a high-order interaction feature vector corresponding to the target object; and
concatenating the feature weight vector, the low-order interaction feature vector, and the high-order interaction feature vector to a fully-connected layer, and determining the predicted CTR at which the target object clicks the content that is to be recommended through weighted summation.