Content data recommendation method and device, computer equipment and storage medium

Abstract

The invention relates to the field of data processing, and discloses a content data recommendation method and device, computer equipment and a storage medium, and the method comprises the steps: carrying out the preprocessing of obtained user data, and obtaining to-be-recommended data; inputting the consumption attribute data, the social attribute data and the access attribute data corresponding to the user into a content preference model, and inputting the traffic service attribute data into a scene recommendation model; performing crowd feature extraction through a first-order crowd clustering model to obtain a first-order crowd classification result, and performing scene adaptation through a scene recommendation model to obtain a theme scene; performing index analysis on the first-ordercrowd classification result and the access attribute data through a second-order index subdivision model to determine a crowd preference label; determining a content recommendation label according tothe crowd preference label and the theme scene; and acquiring content data and recommending to the user. According to the method, crowd feature extraction, index analysis and scene adaptation are carried out on the user data, and accurate recommendation is carried out to the user.

Description

Technical field[0001]The present invention relates to the field of data processing of big data, in particular to a content data recommendation method, device, computer equipment and storage medium.Background technique[0002]With the rapid development of the mobile Internet, it is becoming more and more popular for people to obtain the content information they want from the mobile Internet through the APP in the mobile terminal. However, with the rapid development of the Internet, the amount of information is also increasing significantly, which will cause users to When faced with a large amount of information, it is impossible to quickly obtain the information you really need from the APP, thus reducing the utilization rate of the APP. A better way to solve this problem is to introduce a recommendation method, which can recommend content that users are really interested in from a large amount of information, so that users can obtain the content information they really prefer from the...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of the mobile Internet, it is more and more popular for people to obtain the content information they want from the mobile Internet through the APP in the mobile terminal, but with the rapid development of the Internet, the amount of information is also increasing significantly, which will cause users to When faced with a large amount of information, it is impossible to quickly obtain the information you really need from the APP, thus reducing the usage rate of the APP

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