Optimization system and method for important group identification based on communication big data

By designing an important group identification optimization system based on communication big data, using position zipper fusion algorithm, medium- and high-risk user identification algorithm and spatial coding-based position indexing algorithm, the problem of key group identification in communication big data in the mobile Internet era is solved, efficient storage resource saving and calculation complexity reduction is achieved, and recognition accuracy is improved and real-time query is supported.

CN118312654BActive Publication Date: 2025-03-18湖南省通信网络保障中心
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Patent Information

Application Number
CN202410442952.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-04-12
Publication Date
2025-03-18
Estimated Expiration
2044-04-12

AI Technical Summary

Technical Problem

How to analyze communication big data in the mobile Internet era, efficiently identify user mobility behaviors in key areas, and accurately screen key groups in the area to solve the problem of waste of storage and computing resources caused by the huge amount of signaling data.

Method used

An important population identification optimization system based on communication big data is designed, including the data layer, the data governance layer, the data storage layer and the model processing layer. The location signaling data is compressed through the position zipper fusion algorithm, and the medium and high-risk user identification algorithm identifies risky users, and real-time user screening is realized based on the spatial encoding position index algorithm.

Benefits of technology

It effectively saves storage resources, reduces computing complexity, improves the accuracy of risk group identification, supports real-time query of users by location index, and provides practical and feasible big data technology means for epidemic prevention and control.

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Abstract

The present invention discloses a technical field of crowd positioning and identification, specifically an optimization system and method for identifying important crowds based on communication big data, wherein the system includes a data layer, a data governance layer, a data storage layer and a model processing layer, wherein the data cleaning rule unit is used to filter the data or fill in the missing data fields, and the data aggregation strategy unit is used to aggregate the data disorder problem; the data storage layer includes location-specific data, user risk labels, regional real-time user information, and user real-time location information; a variety of original location signaling data are fused and compressed into a location zipper fusion table through a location zipper fusion algorithm, which can ensure that the amount of user information is not lost and saves dozens of times of storage overhead, thereby providing the possibility for subsequent modeling and analysis of location data, and combining with the epidemic prevention and control scenario to improve the accuracy of selecting risk groups.
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