Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)

<Previous Article In Volume
Next Article In Volume>

Feature Extraction Model of Text Classification In National Defense Science And Technology Tracking

Authors
Kan Li1, *
1Teaching and research support center of Dalian naval vessel academy, Dalian, Liaoning, China
*Corresponding author. Email: likandl@126.com
Corresponding Author
Kan Li
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-058-9_59How to use a DOI?
Keywords
National defense technology; Information extraction; Feature classification; Text classification
Abstract

National Defense Science and technology information is mostly distributed in the form of non classified information. It is an important reference unit for national defense science and technology development planning and technical route. It is an early information resource for national defense scientific research. National Defense Science and technology tracking is a process of measuring, analyzing and extracting national defense science and technology information in different states by using different data analysis technologies based on the information statistics related to national defense science and technology. At present, national defense science and technology tracking lacks effective tracking methods and quantitative analysis tools. This paper uses the method and idea of deep confidence network feature extraction to calculate the correlation between search engine and abstract, so as to monitor, identify, measure and preliminarily extract the texts in different states, such as scientific papers, conference materials, news trends, patent information, policies and regulations, economic and trade information and so on. The research results show that the use of the model can realize the accuracy of tracking, and provide a new idea to improve the tracking speed.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
Series
Advances in Computer Science Research
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-058-9_59
ISSN
2352-538X
DOI
10.2991/978-94-6463-058-9_59How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Kan Li
PY  - 2022
DA  - 2022/12/27
TI  - Feature Extraction Model of Text Classification In National Defense Science And Technology Tracking
BT  - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
PB  - Atlantis Press
SP  - 355
EP  - 360
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-058-9_59
DO  - 10.2991/978-94-6463-058-9_59
ID  - Li2022
ER  -