Content recommendation method and apparatus, electronic device, and storage medium

A content recommendation apparatus, comprising:

• a processor and a memory, the memory storing program code, wherein when executing the program code, the processor is configured to:
• obtain content feedback information of a target object and content feature information of content that is to be recommended in response to a content recommendation request of the target object, the content feedback information comprising at least explicit feedback information and implicit feedback information of the target object on recommended content and object portrait information of the target object;
• respectively input the explicit feedback information and the implicit feedback information into a trained prediction model including a deep feedback interaction component, and obtain behavior preference information of the target object outputted by the deep feedback interaction component;
• perform feature extraction on the behavior preference information, the content feedback information, and the content feature information using the trained prediction model, and obtain a predicted click-through-rate (CTR) that is outputted by the prediction model and at which the target object clicks on the content that is to be recommended;
• and
• determine, according to the predicted CTR at which the target object clicks each piece of content that is to be recommended, recommended content for the target object from the pieces of content that is to be recommended, and transmit the determined recommended content to a terminal device corresponding to the target object.

A non-transitory computer-readable storage medium, comprising program code, when the program code runs on an electronic device, the program code causing the electronic device to perform:

• obtaining content feedback information of a target object and content feature information of content that is to be recommended in response to a content recommendation request of the target object, the content feedback information comprising at least explicit feedback information and implicit feedback information of the target object on recommended content and object portrait information of the target object;
• respectively inputting the explicit feedback information and the implicit feedback information into a trained prediction model including a deep feedback interaction component, and obtaining behavior preference information of the target object outputted by the deep feedback interaction component;
• performing feature extraction on the behavior preference information, the content feedback information, and the content feature information using the trained prediction model, and obtaining a predicted click-through-rate (CTR) that is outputted by the prediction model and at which the target object clicks on the content that is to be recommended;
• and
• determining, according to the predicted CTR, recommended content from the pieces of content that is to be recommended, and transmitting the recommended content to a terminal device corresponding to the target object.