IMSI and face depth fitting method, device, equipment and system

Abstract

The invention relates to an IMSI and face depth fitting method, device, equipment and system. The method comprises the following steps: acquiring face equipment data and electric surrounding base station equipment data; performing position analysis on the geographic position of the face acquisition equipment and the geographic position of the electric surrounding equipment, and determining a spatial association relationship between the face acquisition equipment and the electric surrounding equipment; determining a time association relationship between the personnel and the IMSI according to the face data and the IMSI data; obtaining a space-time association relationship between the personnel and the IMSI according to the space association relationship and the time association relationship; carrying out deep fitting processing on the space-time association relationship by utilizing a pre-trained score increase model and a score attenuation model to obtain an association relationship weight score of the personnel and the IMSI; and determining a depth fitting relationship between the personnel and the IMSI according to the association relationship weight score. According to the method, the association accuracy of the personnel and the IMSI is greatly improved, and the association relationship can be updated in time.

Description

technical field [0001] The present invention relates to the technical field of IMSI and human face interconnection, in particular to a method, device, equipment and system for IMSI and human face depth fitting. Background technique [0002] With the explosive development of artificial intelligence and big data, smart terminals can be seen everywhere. Wherein, IMSI (International Mobile Subscriber Identification Number) is an identification code used to distinguish different users in the cellular network and is not repeated in all cellular networks. As the most common intelligent sensing data, IMSI provides important clues in scenarios such as querying user trajectories, analyzing real mobile phone numbers, locating user locations, and mining user footholds. It is an important supplementary data for user traffic and behavior information. Therefore, being able to associate user information with IMSI information in a timely and accurate manner will provide better data support ...

AI Technical Summary

Problems solved by technology

In the above method, there is no correlation between user information and IMSI information, and it is impossible to mine the hidden effective information between the data; if artificially forcibly associated, there will be problems such as low correlation efficiency, and data cannot be updated in time; further, if IMSI and If the face is simply fitted to the association, since the weight of the association relationship is only a simple linear increase, the accuracy of the association is low

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