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Volumn , Issue , 2009, Pages 25-30

Image spam clustering: An unsupervised approach

Author keywords

Clustering; Computer forensics; Image spam

Indexed keywords

BACKGROUND TEXTURES; COMPUTER FORENSICS; DATA MINING TECHNIQUES; E-MAIL SPAM; FEATURE FUSION; HIERARCHICAL CLUSTERING ALGORITHMS; IMAGE ATTACHMENTS; IMAGE CLUSTERING; INFORMATION HIDING; SPAM EMAILS; SPAM FILTER; SPATIAL LAYOUT; UNSUPERVISED APPROACHES; VISUAL APPEARANCE; VISUAL FEATURE;

EID: 72249099659     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1631081.1631088     Document Type: Conference Paper
Times cited : (5)

References (14)
  • 1
    • 72249111951 scopus 로고    scopus 로고
    • www.cnn.com/2007/TECH/11/29/fbi.botnets
  • 7
    • 57349173529 scopus 로고    scopus 로고
    • Detecting Image-based Email spam using visual features and Near Duplicate Detection
    • Mehta, B., Nangia, S., Gupta, M., and Nejdl, W. 2008. Detecting Image-based Email spam using visual features and Near Duplicate Detection. In Proceedings of the WWW.
    • (2008) Proceedings of the WWW
    • Mehta, B.1    Nangia, S.2    Gupta, M.3    Nejdl, W.4
  • 13
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • Lowe, D. G. 2004. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2): pp. 91-110.
    • (2004) International Journal of Computer Vision , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.