TARU PUBLICATIONS
Journal of Discrete Mathematical Sciences and Cryptography cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

Information security topics extraction and classification method based on modified LDA model

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* Corresponding author · click or hover a name for details

pp. 1207–1212Vol. 26Issue 4June 2023DOI: 10.47974/JDMSC-1613 Crossmark XML
Received:
05 Feb 2022
Accepted:
05 Apr 2022
Published Online:
15 Jul 2023
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-1613
Pages:
1207–1212

Abstract

With the rapid development of social informatization, information plays a pivotal role in people’s lives. The popularization of information has also brought serious information security problems, information security incidents become hot topics for the public. However, it is difficult for the researchers to quickly locate information security incidents because the information security topics are overwhelmed by massive news topics. To solve this problem, a modified LDA model using Python is proposed to improve the classification effect and accuracy of information security topics by perfecting the determination index of the number of topics. Simulation results show that the proposed method can obtain better classification performance compared with the traditional text classification method.

Keywords

Subject Classifications

03C4513C05

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