DocumentCode :
3476309
Title :
Chinese Web Text Classification System Model Based on Naive Bayes
Author :
Gong Zheng ; Yu Tian
Author_Institution :
Coll. of Comput. Sci., Inner Mongolia Univ., Hohhot, China
fYear :
2010
fDate :
7-9 Nov. 2010
Firstpage :
1
Lastpage :
4
Abstract :
Web text classification is the process of determine the text types automatically under a given classification, according to the text content. Web text categorization system is the use of machine learning, knowledge engineering and other related fields of knowledge, access to the web on the text, after text preprocessing, Chinese word segmentation and training classifier, using classification algorithm to implement automatic classification. This paper designed a web of Chinese text categorization system model and system tested, experimental results show that the classification system of the web text categorization with two main characteristics which are efficiency and accuracy.
Keywords :
Bayes methods; Internet; belief networks; knowledge engineering; learning (artificial intelligence); natural language processing; pattern classification; text analysis; word processing; Chinese Web text classification system; Chinese word segmentation; Naive Bayes; Web text categorization system; Web text classification; knowledge engineering; machine learning; text preprocessing; training classifier; Algorithm design and analysis; Classification algorithms; Feature extraction; Machine learning; Support vector machine classification; Text categorization; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
Type :
conf
DOI :
10.1109/ICEEE.2010.5660869
Filename :
5660869
Link To Document :
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