本文選題：貝葉斯算法 + 郵件過濾器�。� 參考：《電子科技大學(xué)》2010年碩士論文

【摘要】： 隨著網(wǎng)絡(luò)的發(fā)展,電子郵件已經(jīng)成為人們?nèi)粘Ｉ钪胁豢苫蛉钡耐ㄓ嵎绞?電子郵件以其方便快捷的特點受到廣大網(wǎng)民的青睞。電子郵件成為人們的主要通訊方式是一種必然的發(fā)展趨勢,但是隨著電子郵件的日益流行,一些不法分子利用這個機會趁機發(fā)送垃圾郵件,向人們傳遞廣告或者非法視頻、圖片等信息,既浪費用戶的時間,又浪費網(wǎng)絡(luò)流量,給用戶的正常工作、生活、學(xué)習(xí)帶來了極大的不便,因此尋找一種切實可行且高效的反垃圾郵件技術(shù)變得尤為重要。 本文應(yīng)實驗室項目的需求,深入研究了國內(nèi)外的主要反垃圾郵件技術(shù),設(shè)計了一個反垃圾郵件系統(tǒng)。通過分析比較當(dāng)前的主流反垃圾郵件技術(shù),本系統(tǒng)決定采用過濾效率較好的基于內(nèi)容的反垃圾郵件技術(shù)。在基于內(nèi)容的反垃圾郵件技術(shù)中,貝葉斯算法的分類效果明顯優(yōu)于其他分類算法,所以本文設(shè)計并實現(xiàn)了一個基于貝葉斯算法的垃圾郵件過濾器,并針對傳統(tǒng)貝葉斯過濾器的不足提出了改進措施,通過將本過濾器改造為基于雙層架構(gòu)的郵件過濾系統(tǒng)來進一步提高系統(tǒng)的準(zhǔn)確率,并解決了在實現(xiàn)貝葉斯過濾器增量學(xué)習(xí)的過程中遇到的問題。 主要工作如下: (1)研究最新的郵件過濾技術(shù),并比較各種技術(shù)的優(yōu)缺點,以選擇效果最好的過濾技術(shù)進行實現(xiàn)。 (2)研究并分析了常用的郵件預(yù)處理技術(shù)(包括郵件解碼,中文分詞,特征詞提取等),并從中選取適用于本系統(tǒng)的技術(shù)。 (3)實現(xiàn)了郵件預(yù)處理過程,包括郵件解碼實現(xiàn),中文分詞實現(xiàn),特征詞提取技術(shù)的實現(xiàn)等。 (4)實現(xiàn)了垃圾郵件過濾器,包括訓(xùn)練過程和測試過程,并通過大量的實驗確定了個參數(shù)值的最佳狀態(tài),從而提高了整個系統(tǒng)的準(zhǔn)確率。 (5)分析貝葉斯過濾器的優(yōu)缺點并提出了改進措施,解決了貝葉斯過濾器在實現(xiàn)增量學(xué)習(xí)時遇到的一些問題。
[Abstract]:With the development of network, email has become an indispensable communication mode in people's daily life. It is an inevitable trend to use email as the main way of communication, but with the increasing popularity of email, some criminals take advantage of this opportunity to send spam and send advertisements or illegal videos to people. Pictures and other information not only waste the user's time but also waste the network traffic and bring great inconvenience to the user's normal work life and study. So it is very important to find a feasible and efficient anti-spam technology. In this paper, the main anti-spam technology at home and abroad is studied, and an anti-spam system is designed. By analyzing and comparing the current mainstream anti-spam technology, this system decided to adopt the content-based anti-spam technology which has better filtering efficiency. In the content-based anti-spam technology, Bayesian algorithm is obviously superior to other classification algorithms, so this paper designs and implements a spam filter based on Bayesian algorithm. Aiming at the shortcomings of the traditional Bayesian filter, the improvement measures are put forward, which can further improve the accuracy of the system by transforming the filter into a two-layer structure based mail filtering system. The problems encountered in the process of realizing Bayesian filter incremental learning are solved. The main tasks are as follows: 1) researching the latest email filtering technology, and comparing the advantages and disadvantages of the various technologies to select the best filtering technology to achieve. 2) the common preprocessing techniques (including mail decoding, Chinese word segmentation, feature extraction and so on) are studied and analyzed, and the technologies suitable for this system are selected. 3) the preprocessing process of mail is realized, including the realization of mail decoding, the realization of Chinese word segmentation and the realization of feature extraction technology. 4) the spam filter is implemented, including the training process and the testing process, and the best state of a parameter value is determined through a large number of experiments, which improves the accuracy of the whole system. 5) the advantages and disadvantages of Bayesian filter are analyzed, and the improvement measures are put forward to solve some problems encountered by Bayesian filter in realizing incremental learning.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2010
【分類號】：TP393.098

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