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Analysis and Application of Bayes Classification Algorithm in the Social Networking Site Information Filtering
Received date: 2014-04-14
Revised date: 2014-05-28
Online published: 2014-07-05
The classification of the document and identify the spam is a very valuable research field. More and more websites began to pay attention to this technology. This paper uses the intelligent algorithm to effectively analyze the garbage information, looking for spammers; through web logs and the published content, determine which advertisers and garbage information promulgator, and delete it. Screening for spam is in fact a process of dividing information into useful information and useless information, the paper attempts to use Bayes classification algorithm to put information into different categories, so the information can be filtered to different classes. The main contribution of the article is aiming at the defects of classification based on rules and method to weed out spam through the analysis of the advertising links, and gives the Bayes classification algorithm and machine learning methods. The experiment results show that, this method is superior to the one based on classification rules.
Li Zhiyi , Shen Zhirui , Yi Meilian . Analysis and Application of Bayes Classification Algorithm in the Social Networking Site Information Filtering[J]. Library and Information Service, 2014 , 58(13) : 100 -106 . DOI: 10.13266/j.issn.0252-3116.2014.13.017
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