Earticle

초록

영어

In this paper, we focus on the problem of signature and role extraction from large-scale mail archives. Due to the huge scale and great diversity of large-scale mail archives, the extraction methods should not only be able to extract signatures and roles accurately without any training data, but also be general enough to work well with large-scale mail archives with different characteristics. To address this problem, we first propose an unsupervised language model based method to identify sig-natures from large numbers of emails, and then present an unsupervised two-stage method to effectively extract roles from the identified signatures. Experimental results on two real-world datasets show that our methods are general and effective for both the signature and role extrac-tion from large-scale mail archives.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Problem Formulation
 4. Unsupervised Signature Extraction
 5. Unsupervised Role Extraction
  5.1 Candidate Role Identification
  5.2 Role Distillation
 6. Experiments
  6.1 Experimental Design
  6.2 Experimental Results
 7. Conclusion
 References

키워드

저자

• Yuan Xiaoqin [ Beijing International Studies University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605