Improved Text Clustering Algorithm and Application in Microblogging Public Opinion Analysis

Author

Yiyang Wang ; Li Wang ; Jing Qi ; Zhong Qian ; Bo Xu ; Chao Lei ; Yuexiang Yang ; Huali Cai

Author_Institution

Sch. of Econ. & Manage., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China

fYear

2013

fDate

3-4 Dec. 2013

Firstpage

27

Lastpage

31

Abstract

Based on K-Means algorithm and agglomerative hierarchical clustering algorithm, improvement was made regarding the use of clustering algorithm in the application of text mining. It was verified that the accuracy and efficiency of hot topic detection had been enhanced via vector representation of the text, text similarity calculation, and implementation of clustering algorithm.

Keywords

Web sites; data mining; pattern clustering; text analysis; vectors; K-means algorithm; agglomerative hierarchical clustering algorithm; hot topic detection; microblogging public opinion analysis; text clustering algorithm; text mining; text similarity calculation; vector representation; Accuracy; Algorithm design and analysis; Clustering algorithms; Educational institutions; Optimization; Partitioning algorithms; Vectors; K-Means algorithm; agglomerative hierarchical clustering; hot topic detection; text clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Engineering (WCSE), 2013 Fourth World Congress on

Conference_Location

Hong Kong

Print_ISBN

978-1-4799-2882-8

Type

conf

DOI

10.1109/WCSE.2013.9

Filename

6754259