title: Detecting Image Spam Using Local Invariant Features and Pyramid Match Kernel
creator: Zuo, Haiqiang
creator: Hu, Weiming
creator: Wu, Ou
creator: Chen, Yunfei
creator: Luo, Guan
description: Image spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters. In this paper, we extract local invariant features of images and run a one-class SVM classifier which uses the pyramid match kernel as the kernel function to detect image spam. Experimental results demonstrate that our algorithm is effective for fighting image spam.
date: 2009-04
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
identifier: http://www2009.eprints.org/174/1/p1187.pdf
identifier: Zuo, Haiqiang <http://www2009.eprints.org/view/author/Zuo=3AHaiqiang=3A=3A.html> and Hu, Weiming <http://www2009.eprints.org/view/author/Hu=3AWeiming=3A=3A.html> and Wu, Ou <http://www2009.eprints.org/view/author/Wu=3AOu=3A=3A.html> and Chen, Yunfei <http://www2009.eprints.org/view/author/Chen=3AYunfei=3A=3A.html> and Luo, Guan <http://www2009.eprints.org/view/author/Luo=3AGuan=3A=3A.html> (2009) Detecting Image Spam Using Local Invariant Features and Pyramid Match Kernel. In: 18th International World Wide Web Conference, April 20th-24th, 2009, Madrid, Spain.
relation: http://www2009.eprints.org/174/