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Research and Implementation based on minimum risk Bayesian multi-level mail filtering system

Author: LiRu
Tutor: LiuPeiYu
School: Shandong Normal University
Course: Computer Software and Theory
Keywords: Content Filtering Minimum risk Bayesian algorithm AdaBoost algorithm Multi-level filtering Shunt filter
CLC: TP393.098
Type: Master's thesis
Year: 2011
Downloads: 39
Quote: 0
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Abstract

With the rapidly growing popularity of the Internet, e-mail occupy an increasingly important position in people's lives. Because of its ease of use, to send a quick, low-cost advantages become very important and popular means of communication in the modern society. But e-mail with a number of negative effects, especially the proliferation of spam increasingly serious occupy system resources, waste of user time and a threat to the security of the network. Has become an urgent problem on the Internet, designed and implemented an effective spam filtering model has important practical significance. For common spam solution from the following four aspects: (1) current spam technology is mostly concentrated in the field of machine learning and data mining, but most of algorithms can not effectively filter spam for spam filtering false negative and false positive problem, the paper proposes an improved minimum risk Bayesian algorithm. The algorithm AdaBoost algorithm combined minimum risk Bayesian algorithm is essentially based classifier using AdaBoost algorithm as the framework of the training the classifier, through training often points the wrong class training samples, and to mark them to to achieve the purpose of mail classification accuracy rate. The combination of the two algorithms to improve the accuracy of the classification and recall, and achieved good filtering effect. (2) In the process of doing experiments, found a problem: not necessarily improved algorithm to filter all information must be better than the original algorithm. Solve the problem, put forward the idea of ??a shunt filter spam. The shunt filter spam based on the content of the message, the first e-mail for the first time a simple classification into different categories, and then a second classification will be divided into good filter such content module, and so divided the use of algorithms that can be better targeted filtering. (3) for a single filtration technology is difficult to effectively filter the spam problem, put forward a multi-level filtering spam. Black / white list, keyword-based, rule-based, based on the contents of a variety of methods such as the integration of the filter on the subject of the message, the text content of the attachment name keywords, the body of the message content and attachments, multi-level filtering can give full play to the advantages of each technology, to achieve the ideal filter effect. (4) the design and content-based multi-level mail filtering system in the Microsoft Visual Studio 2005 platform. Training and test mail samples are derived from the China Education and Research Network Emergency Response Team (CCERT) database of spam and legitimate messages selected from the database 400, 200 spam test, experiments show that the ideology of this e-mail filtering effective.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Computer network > General issues > The application of computer network > E-mail ( E -mail )
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