Efficient Real-Time Information Interaction and Discrimination: Exploration and Application of IT System Algorithms Based on Big Data Processing Technology
DOI: 10.23977/acss.2024.080511 | Downloads: 20 | Views: 1013
Author(s)
Ying Ding 1
Affiliation(s)
1 IT Solution Consulting, MOYI Inc, New York, NY, USA
Corresponding Author
Ying DingABSTRACT
This article discusses an efficient real-time information interactive discrimination system algorithm based on big data processing technology. This paper introduces the big data technology brought by the development of mobile network and social network, and emphasizes the importance of big data in modern information processing. Under the background of big data technology, the paper focuses on the construction and implementation of the computing and data collaboration mechanism to achieve the goal of processing massive data in real time. At the same time, by introducing advanced algorithms and technologies, a method and system of data interaction information discrimination are presented, which can deeply mine the original data from different sources, so as to accurately discriminate the abnormal operation. These research results provide a new algorithm exploration and application path for IT systems, and provide a strong support for efficient real-time information interaction and disagreement. At the same time, it also promotes the application and development of big data technology in various fields, through this system, enterprises and organizations can better cope with the challenges brought by the data explosion, and improve the ability of information processing and decision-making.
KEYWORDS
Big Data Processing Technology, Real-Time Information Interaction, Anomaly Identification, Data Collaboration Mechanism, IT SystemCITE THIS PAPER
Ying Ding, Efficient Real-Time Information Interaction and Discrimination: Exploration and Application of IT System Algorithms Based on Big Data Processing Technology. Advances in Computer, Signals and Systems (2024) Vol. 8: 98-102. DOI: http://dx.doi.org/10.23977/acss.2024.080511.
REFERENCES
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