Data processing method and device, equipment and storage medium

Abstract

The invention discloses a data processing method and device, equipment and a storage medium, and belongs to the technical field of artificial intelligence. In the embodiment of the invention, a mode of obtaining the similarity between the users based on the user portrait data distribution is provided, the target random forest is used for representing the distribution of the user portrait data, andthen similarity analysis is performed on the user portrait data of the two users needing to be compared in a classification mode according to the target random forest. The similarity acquisition is based on user portrait data distribution, so that a preprocessing process is not needed, the data processing flow is simplified, the data processing time can be greatly reduced, and the data processingefficiency is improved. Analysis is made based on the original user portrait data, so that the real situation of the user is reflected, and the similarity is more accurate. The similarity is determined based on the length of the common path between the paths, more data types are considered, the granularity of data processing is finer, and therefore the determined similarity is more accurate.

Description

Technical field[0001]This application relates to the field of artificial intelligence technology, in particular to a data processing method, device, equipment, and storage medium.Background technique[0002]User portraits are also called user roles. As an effective tool for delineating users, contacting user demands and design directions, user portraits have been widely used in various fields. User portrait analysis attempts to use user portrait data to characterize the similarities between users, so as to achieve the business needs of user classification or clustering. Generally, user profile data includes a variety of different data, and different data sources are different, so the nature of these data is different.[0003]At present, data processing methods usually use distance acquisition to analyze the similarity between users. Taking into account the different nature of various data, it is necessary to integrate a variety of preprocessing methods to preprocess user profile data, s...

AI Technical Summary

Problems solved by technology

[0004] The addition of preprocessing in the above method leads to complex, time-consuming, and error-prone data processing procedures, and it is difficult to guarantee the effectiveness of similarity calculations after some non-numeric data is preprocessed.

Therefore, the accuracy of the similarity obtained by the above method is poor, and the acquisition efficiency is low

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