Behavior data prediction method and device, electronic device and computer storage medium

Abstract

The embodiment of the invention discloses a behavior data prediction method and device, an electronic device and a computer storage medium. The method comprises: acquiring feature vectors of historical behavior objects and historical behavior data of the historical behavior objects; obtaining a feature vector of a to-be-predicted behavior object, and calculating the similarity between the featurevector of the to-be-predicted behavior object and the feature vector of the historical behavior object; and determining the historical behavior data of the historical behavior object corresponding tothe similarity meeting a preset condition as the predicted behavior data of the to-be-predicted behavior object. According to the technical scheme, the behavior similarity of a to-be-predicted behavior object and a historical behavior object is analyzed. The historical behavior data of the historical behavior object corresponding to the preset condition similarity is used as the prediction behavior data of the to-be-predicted behavior object, so that the accurate prediction of the to-be-predicted behavior object behavior data is realized, the data prediction accuracy is improved, the troublecaused by unstable test data in the early stage is reduced, and the situation of decision making errors is avoided.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of data processing, and in particular to a behavior data prediction method, device, electronic equipment, and computer storage medium. Background technique [0002] With the development of Internet technology, for many electronic platforms, whenever a new product or new business needs to be released or launched, it is usually selected first to select some users for testing. Users open the product, and before opening it to all users, they need to consider the effect of opening it to all users before making a decision. In the prior art, it is usually based on the relevant data of the previous test users, using forecasting methods such as time series to predict the use effect data of the full amount of users, and make judgments based on this. However, due to the short launch time of new products or new services, the number of test users in the early stage is small, and the data fluctu...

AI Technical Summary

Problems solved by technology

However, due to the short launch time of new products or new services, the number of test users in the early stage is small, and the data fluctuates greatly, it is difficult to accurately predict the effect of opening to other users with the help of traditional prediction methods, which makes the accuracy of data prediction poor. Circumstances that may lead to poor decision-making

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