Title :
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
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;
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
DOI :
10.1109/ISECS.2010.9
