Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)

Analysis of Scientific and Technical Literature in the Big Data

Authors
Wen Zeng, Hui Li, Na Qi
Corresponding Author
Wen Zeng
Available Online March 2018.
DOI
https://doi.org/10.2991/acaai-18.2018.42How to use a DOI?
Keywords
analysis; scientific and technical literature;big data
Abstract

Compared with the others data, scientific and technical literature is multi-source and multiple types. Its content is more emphasis on technical and correlation. In order to analyze and evaluate it, the paper got the value of correlation based on VSM. And it introduced the value of correlation into evaluation indexes of scientific and technical papers and patents in China. Experimental results showed that the method was reasonable and it could improve the traditional evaluation method of scientific and technical literature. The work in this paper will provide a good foundation for the future research.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
978-94-6252-483-5
ISSN
1951-6851
DOI
https://doi.org/10.2991/acaai-18.2018.42How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Wen Zeng
AU  - Hui Li
AU  - Na Qi
PY  - 2018/03
DA  - 2018/03
TI  - Analysis of Scientific and Technical Literature in the Big Data
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 179
EP  - 181
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.42
DO  - https://doi.org/10.2991/acaai-18.2018.42
ID  - Zeng2018/03
ER  -