Recommendation method and device for multimedia information

Abstract

The invention discloses a recommendation method and device for multimedia information and belongs to the technical field of Internet. The recommendation method comprises: determining first multimedia classes interested by a first user according to a historical click action of the multimedia information; determining second multimedia classes which are potentially interested and are not historically clicked by the first user according to each first multimedia class of the first user and a plurality of historical click actions on the multimedia information by the second user; determining a target multimedia class according to the first multimedia classes interested by the first user and the second multimedia classes which are potentially interested by the first user; and recommending the multimedia information of the target multimedia class. When the information is recommended, the determined target multimedia class is more accurate by realizing the multimedia classes of the multimedia information historically clicked by the first user and realizing the multimedia classes which are potentially interested by the first user, so that the clicking rate of the recommended multimedia information can be improved and resources and financial resources can be saved.

Description

technical field [0001] The present invention relates to the field of Internet technologies, and in particular, to a method and device for recommending multimedia information. Background technique [0002] With the rapid growth of the market economy, the market competition is becoming more and more intense. In order to better promote their own products or services, businesses usually produce multimedia information related to their own products or services, and recommend these multimedia information to users through various public platforms. When the multimedia information recommended by the public platform just meets the needs of users, the transaction rate of the product or service can be increased, thereby increasing the income of the merchant. In such a scenario, it is very important how to recommend multimedia information that users are interested in or related to their needs. [0003] In the prior art, when recommending multimedia information, the public platform will ...

AI Technical Summary

Problems solved by technology

[0005] In the prior art, the multimedia category that the user is interested in is determined directly based on the multimedia category that the user has clicked in the most recent period, and the multimedia category clicked in the recent period is due to a small amount of data or there may be accidental reasons. It may not cover the multimedia categories that users are interested in, so it has certain limitations, resulting in inaccurate multimedia categories that users are interested in determined in this way, so that when recommending multimedia information of these multimedia categories, many times The recommended multimedia information cannot attract the user's attention, which leads to the lack of pertinence of the recommended multimedia information, and the low click-through rate of the recommended multimedia information, resulting in a waste of resources and financial resources

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