Information recommendation control method and device, computer equipment and storage medium

Abstract

The invention provides an information recommendation control method. The method comprises the steps of receiving an information recommendation request; in response to the information recommendation request, generating a recommendation score of each accessed object by using a preset recommendation penalty model according to pre-stored historical access data; selecting a to-be-recommended object from the accessed objects according to the recommendation score, obtaining recommendation information of the to-be-recommended object, and making a recommendation strategy; and sending the recommendationinformation to a client for display according to the recommendation strategy. The recommendation score of the accessed object is generated based on the historical access data in combination with thepreset recommendation penalty model, so that the information recommendation efficiency is improved, and the information recommendation is more accurate.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to an information recommendation control method, device, computer equipment and storage medium. Background technique [0002] At present, when users use shopping apps, they often encounter product recommendation services. In the existing technical solutions for product recommendation, the usual practice is to recommend the products with high comprehensive evaluations to the users for all the products to be recommended. , or clicked, or purchased products, these data often lead to a decline in the quality of recommendation results. Generally speaking, the products that users have clicked and browsed will generally not be viewed again, and the products that have been purchased will not be purchased in the short term. [0003] Therefore, in the existing technical solutions, the products to be recommended cannot be obtained according to the user's demand data, and the produc...

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Problems solved by technology

[0003] Therefore, in the existing technical solutions, the products to be recommended cannot be obtained according to the user's demand data, and the products that the user is not interested in are repeatedly recommended, resulting in a decline in the quality of the recommendation results, the results of the products or web pages recommended to the user are not accurate enough, and the recommendation mechanism is not humanized enough.

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