DocumentCode :
2346624
Title :
Identification of Sensitive Information Based on Improved Naive Bayesian Classifier
Author :
Dong, Tao ; Shang, Wenqian
Author_Institution :
Sch. of Comput., Commun. Univ. of China, Beijing, China
fYear :
2011
fDate :
15-19 April 2011
Firstpage :
816
Lastpage :
820
Abstract :
In order to purify the Internet environment, identify the unhealthy and malicious information from the mass network information and achieve the purpose of monitoring the websites efficiently, we use the text preprocessing based on the vector space model and the improved Naive Bayesian classifier to construct a identification system of sensitive information. This system not only identify and classify the sensitive information from the mass of network information, but also provide a practical system and program for monitoring the websites.
Keywords :
Web sites; pattern classification; security of data; text analysis; Internet environment; Web sites; malicious information; naive Bayesian classifier; sensitive information identification; vector space model; Bayesian methods; Classification algorithms; Computational modeling; Support vector machine classification; Text categorization; Training; naive bayes; sensitive information; text classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
Type :
conf
DOI :
10.1109/CSO.2011.149
Filename :
5957782
Link To Document :
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