Internet content pushing method based on big data demand analysis and AI system

Abstract

The embodiment of the invention provides an Internet content pushing method based on big data demand analysis and an AI system. First user portrait feature distribution which does not cover user portrait features corresponding to one or more user community interaction activities of a target user in a plurality of preset user community interaction activities is sent to each content pushing service; each content pushing service executes initial interaction tracking aiming at the target user according to the first user portrait feature distribution, and performs further analysis based on an initial interaction tracking log after generating the initial interaction tracking log, so as to accurately obtain second user portrait feature distribution of the target user; and user portrait features related to community interaction are supplemented in time. Thus, the content pushing configuration rule can be transmitted to the target content pushing service based on the second user portrait feature distribution to request the target content pushing service to perform corresponding Internet content pushing on the target user, and the reliability of Internet content pushing is improved.

Description

technical field [0001] This application relates to the technical fields of artificial intelligence and big data, and specifically relates to an Internet content push method and AI system based on big data demand analysis. Background technique [0002] With the development of Internet network information technology, various Internet online businesses have emerged along with Internet online platforms. In order to increase the usage rate of business products, each Internet online platform needs to deliver various Internet content for different users in order to achieve a higher conversion rate. [0003] At present, most of the Internet content push logic of Internet online platforms lies in user demand analysis, and targeted push is performed based on user demand analysis and prediction results, so as to provide personalized content push experience for different users. However, on the basis of determining and predicting user needs in related technologies, there is a lack of tr...

AI Technical Summary

Problems solved by technology

However, on the basis of determining and predicting user needs in related technologies, there is a lack of tracking and further analysis of relevant target users in the dimension of community interaction activities, resulting in content that is only targeted at the individual dimension of target users in the subsequent Internet content push process Push, not involving content push for the dimension of community activities, which in turn affects the reliability of Internet content push

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