Semi-supervised spam filtering: Does it work?

ACM SIGIR 2008 - 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Proceedings

Volumn , Issue , 2008, Pages 745-746

  Mojdeh, Mona ^a   Cormack, Gordon V ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Self feedback; Semi supervised learning; Spam; Transductive learning

Indexed keywords

EDUCATION; IMAGE RETRIEVAL; INFORMATION RETRIEVAL; INFORMATION RETRIEVAL SYSTEMS; INFORMATION SERVICES; INTERNET; RESEARCH AND DEVELOPMENT MANAGEMENT; SPAMMING; SUPPORT VECTOR MACHINES;

DATA SETS; LABELED DATUM; SELF TRAININGS; SELF-FEEDBACK; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; SEMI-SUPERVISED LEARNING METHODS; SPAM; SPAM FILTERING; TRANSDUCTIVE LEARNING; TRANSDUCTIVE SUPPORT VECTOR MACHINES;

SUPERVISED LEARNING;

EID: 57549112593     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1390334.1390482     Document Type: Conference Paper

References (8)

1. BICKEL, S. ECML-PKDD Discovery Challenge 2006 Overview. In Proc. ECML/PKDD Discovery Challenge Workshop (2006).
2. BRATKO, A., CORMACK, G. V., FILIPIC, B., LYNAM, T. R., AND ZUPAN, B. Spam filtering using statistical data compression models. Journal of Machine Learning Research 6 (2006), 2673-2698.
3. CORMACK, G., AND BRATKO, A. Batch and on-line spam filter evaluation. In CEAS 2006: The Third Conference on Email and Anti-Spam (Mountain View, CA, 2006).
4. CORMACK, G. V. Harnessing unlabeled examples through iterative application of Dynamic Markov Modeling. In Proc. ECML/PKDD Discovery Challenge Workshop (2006).
5. CORMACK, G. V. TREC 2007 Spam Track Overview. In Sixteenth Text REtrieval Conference (TREC-2007) (Gaithersburg, MD, 2007), NIST.
6. CORMACK, G. V., AND LYNAM, T. R. TREC 2005 Spam Track overview. In Fourteenth Text REtrieval Conference (TREC-2005) (Gaithersburg, MD, 2005), NIST.
7. GOODMAN, J., AND TAU YIH, W. Online discriminative spam filter training. In The Third Conference on Email and Anti-Spam (Mountain View, CA, 2006).
8. JOACHIMS, T. Making large-scale support vector machine learning practical. In Advances in Kernel Methods: Support Vector Machines, B. Schölkopf, C. Burges, and A. Smola, Eds. MIT Press, 1998.