Research on Short Text Classification Algorithm Based on Statistics and Rules

Author

Faguo, Zhou ; Fan, Zhang ; Bingru, Yang ; Xingang, Yu

Author_Institution

Sch. of Mech. Electron. & Inf. Eng., Univ. of Min. & Technol. Beijing, Beijing, China

fYear

2010

fDate

29-31 July 2010

Firstpage

3

Lastpage

7

Abstract

In this paper, we introduced the overview of short text research and the short text classification firstly. On the foundation of several common used classic text classification algorithms, mainly according to the major feature extraction methods, the short text classification based on statistics and rules is proposed. Experiments show that this algorithm has better performance than other algorithms. In order to improve the recall rate of short text classification, two-steps classification method is put forward.

Keywords

feature extraction; knowledge acquisition; pattern classification; statistics; text analysis; feature extraction methods; recall rate; rule-based short text classification; short text classification algorithm; statistics-based short text classification; Algorithm design and analysis; Classification algorithms; Feature extraction; Probability; Support vector machine classification; Text categorization; Training; feature extraction; rules; short text; short text classification; statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Commerce and Security (ISECS), 2010 Third International Symposium on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-8231-3

Electronic_ISBN

978-1-4244-8231-3

Type

conf

DOI

10.1109/ISECS.2010.9

Filename

5557448