Share Email Print

Proceedings Paper

Hadoop-based analysis model of network public opinion and its implementation
Author(s): Fei Wang; Peiyu Liu II; Zhenfang Zhu III
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In order to perform network public opinion mining effectively, this paper proposes a Hadoop-based network public opinion analysis model, which applies HDFS file service system to store massive network data distributed, providing fault tolerance and reliability assurance; As the traditional K-means clustering method is too inefficient to process massive data during the clustering process, this paper adopts MapReduce-based K-means distributed topic clustering computation method to process the massive public opinion information through multi-computer cooperation efficiently; And to obtain the information of hot network public opinion in a certain period of time by the analysis of topic heat, and verify the effectiveness of the proposed method by experiments.

Paper Details

Date Published: 26 July 2018
PDF: 10 pages
Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108281H (26 July 2018); doi: 10.1117/12.2502133
Show Author Affiliations
Fei Wang, Shandong Normal Univ. (China)
Peiyu Liu II, Shandong Normal Univ. (China)
Zhenfang Zhu III, Shandong Jiaotong Univ. (China)

Published in SPIE Proceedings Vol. 10828:
Third International Workshop on Pattern Recognition
Xudong Jiang; Zhenxiang Chen; Guojian Chen, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?