Title :
Gender Identification for Chinese E-mail documents
Author :
Gui-fa Teng ; Wen-Qiang Dong ; Jing Yang ; Jian-Bin Ma
Author_Institution :
Agric. Univ. of Hebei, Hebei
Abstract :
In this paper, the method of gender identification for Chinese e-mail documents is described. E-mail documents´ features including linguistic features, format features and structure features were analyzed. The support vector machine algorithm was selected as classification algorithm. Experiments on a set of samples gave promising results, which proved that the method was feasible.
Keywords :
document handling; electronic mail; gender issues; natural languages; support vector machines; Chinese e-mail documents; format features; gender identification; linguistic features; structure features; support vector machine algorithm; Classification algorithms; Electronic mail; Information science; Machine learning algorithms; Pediatrics; Physiology; Postal services; Support vector machine classification; Support vector machines; Terminology;
Conference_Titel :
Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
Conference_Location :
Kumamoto
Print_ISBN :
0-7695-2882-1
DOI :
10.1109/ICICIC.2007.327
