Research on Filtration System of Network Negative Information on the Basis of Naive Bayes

Xi Ai Yan; Jin Min Yang

doi:10.4028/www.scientific.net/AMR.271-273.911

Paper Titles

Analysis Online Shopping Behavior of Consumer Using Decision Tree
p.891

Investment Risk Analysis on the Widespread Use of Electric Vehicles
p.895

Signal Process Technology of Omni-Directional Level Posture
p.900

Exploration of Several Difficult Croblems in Compiling Drawing Used AutoCAD
p.904

Research on Filtration System of Network Negative Information on the Basis of Naive Bayes
p.911

Analysis of Self-Adapted Fault-Tolerant System in Distributed Information Resource Management
p.917

The Research on the Construction of a Virtual Community Knowledge Base
p.923

Apply TEM to Mining Exploration of Crises Iron Mine in the Area of Xiangshui River
p.929

The Cluster Design of MMOG Servers on Mobile Platform
p.933

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 271-273Research on Filtration System of Network Negative...

Research on Filtration System of Network Negative Information on the Basis of Naive Bayes

Abstract:

The difficulty of filtrating network negative information lies in how to classify information correctly. As one of the classification method with the advantage of strong robustness and good understandability in the field of pattern classification, Naïve Bayes has been used widely. A method for filtrating network negative information on the basis of Naïve Bayes, improvement proposals aiming at the disadvantages of Naïve Bayes and amelioration of erroneous judgment of negative information by setting threshold value k have been put forward in this article. The experiment shows that by adjusting threshold value k can the integrity of the system can be optimum and can favorable application effects be achieved.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 271-273)

Pages:

911-916

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.271-273.911

Citation:

Cite this paper

Online since:

July 2011

Authors:

Xi Ai Yan, Jin Min Yang

Keywords:

Filtration, Naive Bayes, Negative Information, Probability Statistics

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Lewis D D. Naive Bayes at forty : the independence assumption in information retrieval [ C] . Proc of the 10th European Conf on Machine Learning . [ s. l. ]: Springer-Verlag, 1998: 4-15.

DOI: 10.1007/bfb0026666

Google Scholar

[2] Sahami M, Dumais S, Heckerman D, et al. A Bayesian approach to filtering junk E-mail[ C]. Proc of AAAI Workshop on Learning for Tex t Categorization. Madison Wisconisin: [ s. n. ] , 1998: 55-62.

Google Scholar

[3] Zhang H. Exploring Cond itions for the Optimality of Naive Bayes. International Journal of Pattern Recogn ition and Artificial Intelligence, 2005, 19( 2) : 183~ 198.

DOI: 10.1142/s0218001405003983

Google Scholar

[4] Heckerman D. Geigerand D. M. Chickering. Learning Bayesian networks, Combination of Knowledge and Statistical Data[J], Machine Learning, 1995, 20(3); 197-243.

DOI: 10.1007/bf00994016

Google Scholar

[5] Salton G, Wong A Yang CS. A Vector Space Model for Automatic Indexing [J]. Communication of the ACM. 1995, (1): 2-8.

Google Scholar

[6] Schneidet K. A Comparison of Event Models for Naïve Bayes anti-spam Email Fitering[C]. Proc of the 10th Conference of the European Chapter of the Association for Computatinal Linguistics (EACL'03), 2003: 307-314.

DOI: 10.3115/1067807.1067848

Google Scholar