Recommendation method and device, equipment and computer storage medium

Abstract

The embodiment of the invention provides a recommendation method and device, equipment and a computer storage medium, and the method comprises the steps of determining an interest label of a to-be-recommended user based on the obtained DPI data of the to-be-recommended user; determining a candidate recommendation set based on at least two models, the interest label and the feature information of the multimedia to be recommended; determining a target recommendation result from the candidate recommendation set at least based on the category information of the to-be-recommended user; and sendingthe target recommendation result to the terminal of the to-be-recommended user. Therefore, the interest of the user is mined by utilizing the DPI data to supplement the dimension characteristics of the user, so that the authenticity problem of the traditional user dimension demographic information is solved; two models are adopted to obtain a candidate recommendation set, so that the diversity ofthe candidate recommendation set is improved while the recall rate is ensured; the target recommendation result is obtained by using the thought of classifying the users, so that the recommendation for the users is more targeted, and the user experience is improved.

Description

technical field [0001] The present application belongs to the technical field of information processing, and involves but is not limited to a recommendation method, device, equipment and computer storage medium. Background technique [0002] With the continuous development of mobile communication technology, people can browse all kinds of information on the Internet at will, such as entertainment multimedia information, or household daily necessities information, etc., and the network will also recommend various items to users according to their cost performance or uniqueness. The user chooses. [0003] There are two most mature recommendation algorithms in the existing recommendation system, namely collaborative filtering algorithm and recommendation system based on deep learning. The collaborative filtering algorithm is divided into user-based collaborative filtering and item-based collaborative filtering, but these two Collaborative filtering can only recommend products ...

AI Technical Summary

Problems solved by technology

[0005] In view of this, the main purpose of the embodiment of the present application is to provide a recommendation method and device, equipment and computer storage medium, which can at least solve the problem of the authenticity of user statistical information and the diversity of recommended content, and improve user experience.

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