Directional advertisement putting method and device and computer readable storage medium

Abstract

The invention relates to the artificial intelligence, and provides a directional advertisement putting method and device and a computer readable storage medium. The method comprises the steps of calculating the similarity of the label vectors of two users, and obtaining a score 1; calculating the similarity of the two user behavior vectors to obtain a score 2; modeling a user vector by using an alternating least square algorithm, obtaining the user vector and an advertisement vector by using a random gradient descent optimization algorithm, calculating the similarity of the user vectors of twousers to obtain a score 3, and weighting the score 1 to the score 3 linearly to obtain a score 4; carrying out XGBOOST, SVM and GBDT on the user behavior vector, the user interest label vector and the user vector respectively to obtain the corresponding scores as FM input, obtaining a score 5, and weighting the score 4 and the score 5, outputting the final user similarity, comparing the final user similarity with a similarity threshold, and selecting the user higher than the similarity threshold as a target customer group.

Description

technical field [0001] The present invention relates to artificial intelligence, in particular to a targeted advertisement delivery method, device and computer-readable storage medium. Background technique [0002] With the development of network technology, social network has become one of the important communication platforms. Message push has been used more and more. Push technology refers to the technology of sending information to users through the Internet according to certain sending rules and related standards and protocols. E-commerce vendors push all kinds of information to users' smart mobile terminals one after another. However, at present, targeted advertising basically targets people based on user interests or labels; and the target customer group is a behavior that most people in the group have, which will make the coverage of the target customer group very low. Compared with Internet users, users of financial products have less richness of user behavior da...

AI Technical Summary

Problems solved by technology

However, at present, targeted advertising basically targets people based on user interests or labels; and the target customer group is a behavior that most people in the group have, which will make the coverage of the target customer group very low

Compared with Internet users, users of financial products have less richness in user behavior data, which leads to certain challenges in mining user interests and tags.

In real scenarios, target customer groups often do not have very clear boundaries and distinctions, and it is difficult to delineate target customer groups using individual interests and tags of users

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