Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)

The Microblog Public Opinion Analysis Based on the SVM and the LDA Model Combining

Authors
Weilin Xu, Zong Zhu, Li Gao, Jinling Liu
Corresponding Author
Weilin Xu
Available Online July 2016.
DOI
https://doi.org/10.2991/iccia-17.2017.14How to use a DOI?
Keywords
SVM model; LDA model; Microblog; Public opinion; Clustering.
Abstract
In view of the LDA model, the superiority of long text clustering to Microblog about the use of the user and time to build a long text. According to implied rich semantic information in text and traditional text clustering makes because of the high dimension calculation results inaccurate faults, the SVM model is given and the LDA model combining the similarity, the last is the use of K - Means algorithm for clustering. Combining the experimental results show that the SVM and the LDA model significantly improves the clustering quality and stability
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Proceedings
2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
Part of series
Advances in Computer Science Research
Publication Date
July 2016
ISBN
978-94-6252-361-6
ISSN
2352-538X
DOI
https://doi.org/10.2991/iccia-17.2017.14How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Weilin Xu
AU  - Zong Zhu
AU  - Li Gao
AU  - Jinling Liu
PY  - 2016/07
DA  - 2016/07
TI  - The Microblog Public Opinion Analysis Based on the SVM and the LDA Model Combining
BT  - 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017)
PB  - Atlantis Press
SP  - 95
EP  - 98
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-17.2017.14
DO  - https://doi.org/10.2991/iccia-17.2017.14
ID  - Xu2016/07
ER  -