A case-based technique for tracking concept drift in spam filtering
Open Access
- 13 April 2005
- journal article
- Published by Elsevier in Knowledge-Based Systems
- Vol. 18 (4-5), 187-195
- https://doi.org/10.1016/j.knosys.2004.10.002
Abstract
No abstract availableKeywords
This publication has 14 references indexed in Scilit:
- Dynamic weighted majority: a new ensemble method for tracking concept driftPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Using latent semantic indexing to filter spamPublished by Association for Computing Machinery (ACM) ,2003
- A Memory-Based Approach to Anti-Spam Filtering for Mailing ListsInformation Retrieval Journal, 2003
- Mining time-changing data streamsPublished by Association for Computing Machinery (ACM) ,2001
- Adaptive information filteringPublished by Association for Computing Machinery (ACM) ,1999
- Support vector machines for spam categorizationIEEE Transactions on Neural Networks, 1999
- Extracting Hidden ContextMachine Learning, 1998
- Tolerating Concept and Sampling Shift in Lazy Learning Using Prediction Error Context SwitchingPublished by Springer Nature ,1997
- Instance-based learning algorithmsMachine Learning, 1991
- Incremental learning from noisy dataMachine Learning, 1986