Research on Document Clustering from Internet Public Opinions

DOI

10.2991/iccsae-15.2016.180How to use a DOI?

Keywords

topic discovery; clustering method

Abstract

Generally, in the traditional multilingual topic discovery, it is the multilingual text for a single goal of the conversion and then clustering. On this basis, we have constructed a custom dictionary for the people with the highest percentage of Chinese, Japanese and English in this paper. At the same time, we have improved the single-pass clustering algorithm in single language. And considering the characteristics of news effectiveness, we have proposed a multilingual text composite clustering algorithm based on fusion time impact factor, which makes the clustering analysis results more reasonable, and better reflects the characteristics of the effectiveness of network news.

Copyright

© 2016, 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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TY  - CONF
AU  - Ximei Wang
PY  - 2016/02
DA  - 2016/02
TI  - Research on Document Clustering from Internet Public Opinions
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 981
EP  - 984
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.180
DO  - 10.2991/iccsae-15.2016.180
ID  - Wang2016/02
ER  -