A method of micro-blog information classification based on mixed characteristics

Author

Xiang Gao ; Lei Liu ; Shengluan Hou

Author_Institution

Coll. of Appl. Sci., Beijing Univ. of Technol., Beijing, China

fYear

2013

fDate

23-25 July 2013

Firstpage

853

Lastpage

857

Abstract

In micro-blogging services such as the micro-blog, the users may get overwhelmed by large amounts of the data. An automatic method of solving this problem is the micro-blog information classification. The traditional classification of micro-blog also lost some useful information of micro-blogging. And the weight calculation and feature selection of traditional method is not an adaptive way to solve the micro-blog information classification. In order to solve the problems above, this paper presents a method of micro-blog information classification using the mixed characteristics. On the basis of the statistical methods of chi-square (CHI), we use the frequency to improve the feature selection and the weight calculation method. The experimental results show that the method is useful to improve micro-blog information classification.

Keywords

Web sites; classification; statistical analysis; chi-square; feature selection; microblog information classification; mixed characteristics; statistical methods; weight calculation; weight calculation method; Accuracy; Classification algorithms; Educational institutions; Kernel; Semantics; Support vector machines; Text categorization; Micro-blog information classification; chi-square statistic; mixed characteristics; tf∗idf;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2013 Ninth International Conference on

Conference_Location

Shenyang

Type

conf

DOI

10.1109/ICNC.2013.6818095

Filename

6818095