DocumentCode :
643914
Title :
Micro-blog category based on feature-words category dispersion
Author :
Yingyou Chen ; Qing Wu
Author_Institution :
Dept. of Comput., Hangzhou Dianzi Univ., Hangzhou, China
Volume :
01
fYear :
2012
fDate :
Oct. 30 2012-Nov. 1 2012
Firstpage :
105
Lastpage :
108
Abstract :
The micro-blog information classification is an important pretreatment in micro-blog data processing work. Due to the unique properties of the micro-blog text, there are some limitations when use traditional classification to deal with it. Consider to a single microblog text brief which contains less effective feature-words, and the content compare spoken of the features, this paper proposed to use similar words and collocations to extend the text feature-words, reducing the possibility of feature loss. For the feature of information selection and weight calculation, proposed one kind text classification methods which based on the feature-words category dispersion and dispersion degree. The experiments show that the propose classification method achieves good effects in the classification of micro-blog text, and has better applicability in microblog text classification scene.
Keywords :
Web sites; text analysis; data processing work pretreatment; dispersion degree; feature loss; feature-words category dispersion; information selection; micro-blog information classification; text classification methods; weight calculation; Accuracy; Computers; Dispersion; Support vector machine classification; Text categorization; Training; Vectors; Category dispersed; Feature-word extension; Micro-blog text classification; Term weight;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
Type :
conf
DOI :
10.1109/CCIS.2012.6664377
Filename :
6664377
Link To Document :
بازگشت