DocumentCode :
2137836
Title :
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
Link To Document :
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