Earticle

초록

영어

In this paper, we constructed a two-phase spam-mail filtering system based on the lexical and conceptual information. There are two kinds of information that can distinguish the spam mail from the legitimate mail. The definite information is the mail sender's information, URL, a certain spam list, and the less definite information is the word list and concept codes extracted from the mail body. We first classified the spam mail by using the definite information, and then used the less definite information. We used the lexical information and concept codes contained in the email body for SVM learning in the phase. According to our results the spam precision was increased if more lexical information was used as features, and the spam recall was increased when the concept codes were included in features as well.

목차

Abstract
 1. Introduction
 2. Training Phase
  2.1. Definite Information
  2.2. Less Definite Information 
  2.3. Kadokawa Thesaurus
  2.4. Constructing Feature Vectors 
 3. Applying Phase
 4. Experiments
 5. Conclusion
 References

키워드

저자

• Kang, Sin-Jae [ School of Computer and Information Technology, Daegu University ]
• Kim, Jong-Wan [ School of Computer and Information Technology, Daegu University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국정보기술응용학회 학술대회

• 간기

  부정기

• 수록기간

  2001~2011

• 십진분류

  KDC 005 DDC 005