Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System
Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces ar...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6695484 |
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| _version_ | 1832550849209958400 |
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| author | Lina Yu Chunwei Wang Huixian Chang Sheng Shen Fang Hou Yingwei Li |
| author_facet | Lina Yu Chunwei Wang Huixian Chang Sheng Shen Fang Hou Yingwei Li |
| author_sort | Lina Yu |
| collection | DOAJ |
| description | Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work efficiency and accuracy of classification and gradation. At the same time, the differences, advantages, and disadvantages of K-NN (K-Nearest Neighbors), DT (Decision Tree), and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises. |
| format | Article |
| id | doaj-art-902468da40a6482b90b99b3af7f751fa |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-902468da40a6482b90b99b3af7f751fa2025-02-03T06:05:40ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/66954846695484Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation SystemLina Yu0Chunwei Wang1Huixian Chang2Sheng Shen3Fang Hou4Yingwei Li5School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaSchool of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaSchool of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaSchool of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaSchool of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaSchool of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, ChinaClassification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work efficiency and accuracy of classification and gradation. At the same time, the differences, advantages, and disadvantages of K-NN (K-Nearest Neighbors), DT (Decision Tree), and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises.http://dx.doi.org/10.1155/2020/6695484 |
| spellingShingle | Lina Yu Chunwei Wang Huixian Chang Sheng Shen Fang Hou Yingwei Li Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System Complexity |
| title | Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System |
| title_full | Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System |
| title_fullStr | Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System |
| title_full_unstemmed | Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System |
| title_short | Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System |
| title_sort | application research of intelligent classification technology in enterprise data classification and gradation system |
| url | http://dx.doi.org/10.1155/2020/6695484 |
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