13 search results - page 2 / 3 » A case for unsupervised-learning-based spam filtering |
UM
2005
Springer
13 years 11 months ago
2005
Springer
The A theory of user expectation of system interaction is introduced in the context of User Adapted Interfaces. The usability of an intelligent email client that learns to filter s...
EWCBR
2004
Springer
13 years 11 months ago
2004
Springer
Because of the volume of spam email and its evolving nature, any deployed Machine Learning-based spam filtering system will need to have procedures for case-base maintenance. Key t...
ICCBR
2007
Springer
13 years 11 months ago
2007
Springer
In this paper, we compare case-based spam filters, focusing on their resilience to concept drift. In particular, we evaluate how to track concept drift using a case-based spam fi...
PRL
2008
13 years 5 months ago
2008
In this paper, we propose spam e-mail filtering methods having high accuracies and low time complexities. The methods are based on the n-gram approach and a heuristics which is re...
AI
2010
Springer
13 years 10 months ago
2010
Springer
Many classification techniques used for identifying spam emails, treat spam filtering as a binary classification problem. That is, the incoming email is either spam or non-spam....