Object recommendation method and device, storage medium and computer equipment

Abstract

Embodiments of the invention provide an object recommendation method and device, a storage medium and computer equipment, and the method comprises the steps: obtaining various attribute information ofa target object, constructing a feature vector of the target object, and inputting the feature vector into a prediction module according to an operation sequence of each target object to obtain a prediction feature vector.Thus, the expression content of the feature vectors is enriched, the operation sequence of all the target objects is considered in the model calculation process, and the accuracy of the prediction result is improved; moreover, since the plurality of objects output by the application platform share one piece of attribute information, the number of parameters for training theprediction model is greatly reduced, the model training difficulty is reduced, and the method can be suitable for a large number of application scenarios.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to an object recommendation method, device, storage medium and computer equipment. Background technique [0002] In recent years, the popularization of the Internet has brought a large amount of information to users. While satisfying users' needs for information, users cannot quickly find useful information due to the large amount of information, which reduces the efficiency of information use. In this regard, in the fields of news, business, entertainment, etc., it is proposed to use the recommendation system to analyze the user's behavior data on the corresponding application platform, predict the user's preferences, and accordingly filter out the information that the user may be interested in in the future and push it to the user. Help users quickly and accurately select the information they need. [0003] Among them, in the existing recommendation system, it is ...

AI Technical Summary

Problems solved by technology

[0004] However, the number of objects that the application platform actually has is often very large, which will lead to a sharp increase in the number of parameters of the prediction model, which greatly increases the difficulty of training the prediction model, and because a word vector often cannot accurately represent the content of the object, it will It will affect the accuracy of the prediction results actually obtained by the prediction model, so that the object pushed to the user may not be the object of interest to the user

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