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研究生:蔡宗翰
研究生(外文):TzongHan Tsai
論文名稱:機器分類學習技術於個人化電子郵件助理之研究
論文名稱(外文):Machine Learning Classification Techniques for Personalized Email Agents
指導教授:許永真許永真引用關係
指導教授(外文):Yung-jen Hsu
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:資訊工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:1999
畢業學年度:87
語文別:英文
論文頁數:86
中文關鍵詞:電子郵件助理機器學習個人化文件分類
外文關鍵詞:email agentmachine learningpersonalizetext classification
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本論文針對電子郵件分類與重要性預測的問題,提出了一個人化電子郵件助理系統:助理系統會學習使用者的分類習慣以及重要性歸類方法。並以此系統為基礎,進行分類準確率與重要性預測正確率的實驗。
本系統的核心是信件分類模組,利用在文件分類上有良好效果的 naive Bayes classifier 來實作。同時將信件表述成許多種不同的方式,以測試何種方式可以使郵件分類的正確率最高。
在重要性預測方面,如果將郵件的重要性分為三種,高、中、低,那麼郵件的重要性預測問題也可以利用分類問題來解決,因此對此我們也進行與分類問題同樣的實驗。針對網際網路上目前氾濫的廣告信件,我們也測試了系統核心過濾廣告信件的能力。
總之,經過一段時間的學習後,電子郵件助理便可以提供給個人越來越貼心的服務。
This thesis discusses the problem of email classification and prioritization. An email agent system is implemented. It can learn
a user''s customs for email classification. Based on this system, experiments of classification correctness and importance prediction
are done.
The kernal of this system is mail classification module. The naive Bayes classifier, which performs well on text classification is applied. Besides, we represent emails as several different forms to test which form is the best for improving correctness of classification .
In the aspect of importance prediction, if we divide the importance of emails into three levels, high, midium, and low, the problem can reduce to classificationo problem. As a result, we do the same experiments as classification problem. We also use our system to test the ability of jumk mail filtering.
In summary, after learning time, email agent can provide users better and better services.
CHAPTER 1 INTRODUCTION1
1.1PROBLEM2
1.2THESIS OVERVIEW5
CHAPTER 2 RELATED WORK9
2.1PERSONALIZED INFORMATION FILTERING9
2.2INTERFACE AGENTS13
2.3PRESENT EMAIL AGENTS15
2.4SUMMARY18
CHAPTER 3 MACHINE LEARNING FOR EMAIL CLASSIFICATION21
3.1DEFINITION OF THE NAIVE BAYES CLASSIFIER22
3.2REPRESENTATION OF A MESSAGE23
3.3CLASSIFICATION ALGORITHM26
CHAPTER 4 EXPERIMENTAL EVALUATION FOR CLASSIFICATION33
4.1CLASSIFIER IMPLEMENTATION33
4.2EXPERIMENTAL EVALUATION37
CHAPTER 5 PRIORITIZATION43
5.1CONCEPT AND IMPLEMENTATION43
5.2EXPERIMENTAL EVALUATION FOR PRIORITIZATION44
5.3EXPERIMENTAL EVALUATION FOR SPAM FILTERING45
CHAPTER 6 DEMONSTRATION49
6.1INSTALLATION49
6.2MAILSERVER PROPERTIES SETTING50
6.3HOW TO USE MAILKEEPER?51
CHAPTER 7 CONCLUSION AND FUTURE WORK55
7.1CONCLUSION55
7.2FUTURE WORK56
APPENDIX A DISCUSSION OF EMAIL AGENT SYSTEM ARCHITECTURE59
A.1MULTI-USER MAILKEEPER59
A.2GATEWAY60
A.2.1MAIL RETRIEVE AND PROCESS MODULE61
A.2.2MESSAGE DELIVER62
A.3CLIENT62
A.4COMMUNICATION PROTOCOL63
A.5DATA FLOW66
APPENDIX B CONDITIONAL PROBABILITY69
BIBLIOGRAPHY73
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