KEYWORDS: Data processing, Distributed computing, Data acquisition, Real-time computing, Industrial applications, Data transmission, Data analysis, Clouds, Data communications, Data storage
In the context of the continuous development of information technology, the 5G era has ushered in a new intuation, the rapid development of mobile Internet and the continuous richness of business types, the data generated by users in the process of using various types of business has multiplied, the emergence of massive data and the change of data structure. It brings great challenges to operators' data management, data collection, data statistical analysis, data processing and data operation and maintenance. How to deal with these data effectively and efficiently has become the key to operators' improvement of operational efficiency and service quality. Edge computing, as a new computing mode, assigns computing tasks to the edge of the network, making data processing and analysis more real-time and efficient. This paper provides strong technical support for the implementation of edge computing through the characteristics of 5G network, such as high speed, low latency and large connection. It proposes a method to improve the data processing efficiency of operators based on 5G edge computing technology. It adopts theoretical analysis and experiments to carry out comprehensive research, effectively improve the processing of massive data, reduce cost and increase efficiency. And realize the security and efficiency of data, enhance the market competitiveness, and thus improve the user experience.
This paper focuses on optimizing integer data formatted output based on high-performance parsing software. We provide three methods for formatting integer fields and compare them with standard library functions sprintf in performance. These methods are experimentally proven to have reasonable practicality and usability.
In this paper, aiming at the uniqueness check of standard address import in mobile resource management system, a standard address intelligent import method based on Geocoding and TF-IDF is proposed. Address names are standardized through Geocoding to uniform the naming rules of addresses at all levels and remove the interference of non-mandatory level names on results. The address names recorded in the system are used as the address database, and the similarity of address names is calculated through TF-IDF. The address names with high similarity are filtered out, and then the address names are judged manually. Experiments show that this method can effectively improve the accuracy of uniqueness verification and greatly reduce the manual workload.
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