A Study on Reorganization of Korean Traditional Knowledge Resource Classification(kTKRC)

Myeongcheol, Jeong; Oksun, An; Lee, Hyeongyeong

doi:10.34122/jip.2019.12.14.4.275

Cited by 1 publication

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“…ese tags will not have much help and influence on the positioning of resource topics, but not all markers are meaningless, for example, starting tags such as <title> </Title>, <strong> </strong> may provide some reference information for the classification of network information resources. e other is the controllable spam information, which mainly includes navigation bar, advertisement, picture link, copyright, and other information [15,16].…”

Section: Filtering the Original Noisementioning

confidence: 99%

Research on Classification Method of Network Resources Based on Modified SVM Algorithm

Zhang¹,

Jingchao²,

Zhang

2021

Security and Communication Networks

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According to the traditional classification method of network capital resources, there are some problems such as low efficiency, low recall rate, and low precision rate of information. Therefore, this paper proposes a new classification method of network capital resources based on SVM algorithm. Firstly, the original sample data are analyzed by principal component analysis to realize the design of resource classification process. Then, the dimension reduction of network resources data is realized by word segmentation and denoising. Thirdly, the reduced sample data are trained by the SVM classifier, and the best parameters of the reduced data are obtained by the grid search method. Lastly, the search range of SVM classifier parameters based on the original sample data is reset, so as to quickly obtain the best SVM classifier parameters of the original sample data and realize the classification. The experimental results show that this method can improve the recall and precision of network resource information and shorten the classification time of network resources.

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Section: Filtering the Original Noisementioning

confidence: 99%