Abstract
There are a few key benefits of a case-based approach to spam
filtering. First, the many different sub-types of spam suggest that a local
learner, such as Case-Based Reasoning (CBR) will perform well. Second, the
lazy approach to learning in CBR allows for easy updating as new types of
spam arrive. Third, the case-based approach to spam filtering allows for the
sharing of cases and thus a sharing of the effort of labeling email as spam. In
this paper we introduce a case-based approach to spam filtering and present
preliminary evidence of the first two of these advantages.
filtering. First, the many different sub-types of spam suggest that a local
learner, such as Case-Based Reasoning (CBR) will perform well. Second, the
lazy approach to learning in CBR allows for easy updating as new types of
spam arrive. Third, the case-based approach to spam filtering allows for the
sharing of cases and thus a sharing of the effort of labeling email as spam. In
this paper we introduce a case-based approach to spam filtering and present
preliminary evidence of the first two of these advantages.
| Original language | Undefined/Unknown |
|---|---|
| Title of host publication | Case-Based Reasoning Research and Development |
| Subtitle of host publication | 5th International Conference on Case-Based Reasoning, ICCBR 2003, Trondheim, Norway, June 23-26, 2003, Proceedings |
| Editors | Kevin D. Ashley, Derek G. Bridge |
| Publisher | Springer Nature |
| Publication status | Published - 2003 |