Analysis of the Discipline System Model of Scientific Information Technology Based on Big Data Mining Algorithms

In order to improve the construction effect of the subject system of the history of science and technology with Chinese characteristics, this paper combines the big data technology to build the subject system of the history of science and technology with Chinese characteristics. This paper proposes a maximum point finding probability algorithm for massive point set data, and proves the reliability of the algorithm. Moreover, this paper introduces matrix distance and objectively weights the comprehensive evaluation results of different years. In addition, this paper conducts simulation experiment research with algorithm, and verifies the effect of the subject system model of the history of science and technology with Chinese characteristics based on big data technology. The research results show that the subject system model of the history of science and technology with Chinese characteristics based on big data technology proposed in this paper can play an important role in the construction of the subject system of the history of science and technology with Chinese characteristics.

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Publication Details

Journal
Computer Fraud & Security
Published
2024-12-25
DOI
https://doi.org/10.52710/cfs.156
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
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article

Analysis of the Discipline System Model of Scientific Information Technology Based on Big Data Mining Algorithms

Meiqiu Liu
Computer Fraud & Security
E-commerce and Technology Innovations
article

Analysis of the Discipline System Model of Scientific Information Technology Based on Big Data Mining Algorithms

Meiqiu Liu
article en

Abstract

In order to improve the construction effect of the subject system of the history of science and technology with Chinese characteristics, this paper combines the big data technology to build the subject system of the history of science and technology with Chinese characteristics. This paper proposes a maximum point finding probability algorithm for massive point set data, and proves the reliability of the algorithm. Moreover, this paper introduces matrix distance and objectively weights the comprehensive evaluation results of different years. In addition, this paper conducts simulation experiment research with algorithm, and verifies the effect of the subject system model of the history of science and technology with Chinese characteristics based on big data technology. The research results show that the subject system model of the history of science and technology with Chinese characteristics based on big data technology proposed in this paper can play an important role in the construction of the subject system of the history of science and technology with Chinese characteristics.

Computer Fraud & Security
Hohhot Minzu College (CN)
Openalex Percentile: Top 51%
E-commerce and Technology Innovations
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Analysis of the Discipline System Model of Scientific Information Technology Based on Big Data Mining Algorithms — Meiqiu Liu · Computer Fraud & Security (2024) | TGRS Research Map | TGRS