Distributed intelligent data management system and method based on cloud computing

By using a distributed intelligent data management system based on cloud computing, signaling data is parsed using time slicing and snapshot mapping, and an electronic fence logic network is constructed. By combining signal dwell confidence and reverse sliding time window verification, the problem of inaccurate user behavior recognition in existing technologies is solved, enabling precise delivery of personalized services and improving user experience and information delivery efficiency.

CN121664876APending Publication Date: 2026-03-13NANJING HEJIANG INFORMATION CONSULTING CO LTD
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Patent Information

Application Number
CN202511824985.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-05
Publication Date
2026-03-13

AI Technical Summary

Technical Problem

Existing intelligent information push solutions cannot accurately identify real-time behavioral differences of users in specific areas and lack continuous and refined analysis of user terminal signaling data, resulting in a lack of targeted information push and difficulty in guaranteeing user experience.

Method used

By using a cloud-based distributed intelligent data management system, user terminal signaling data is parsed using time slicing and snapshot mapping methods, an electronic fence logical network is constructed, and personalized service message data packets are generated by combining signal dwell confidence and reverse sliding time window verification.

Benefits of technology

It enables the precise construction of user behavior trajectory data, improves the accuracy of user dwell behavior identification and the security and targeting of personalized services, and enhances the efficiency of information push and user experience.

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Abstract

The invention provides a distributed intelligent data management system and method based on cloud computing, and relates to the technical field of intelligent communication. The method comprises the following steps: performing time slice segmentation and snapshot mapping analysis processing on a user terminal interaction signaling data stream to obtain an accurate and continuous signaling track data set; constructing an electronic fence logic network containing a parent region grid and a child hotspot grid, calculating a user terminal signal residence confidence coefficient, and screening out a target user terminal meeting a deep residence condition; calling target user terminal interaction information, executing rule mutual exclusion verification of the reverse sliding time window, and generating a service release instruction; and calling the cloud structured data template to render content in real time, and scheduling and issuing a personalized service message data packet. According to the invention, accurate identification of user behaviors and safe and efficient pushing of personalized information are realized, and service accuracy and user experience are remarkably improved.
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