Name
Abstract | ||
|---|---|---|
We report on the construction of an ontology that applies rules for identification of features to be used foremail classification. The associated probabilities forthese features are then calculated from the training setof emails and used as part of the feature vectors for anunderlying Bayesian classifier. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ITCC.2003.1197525 | ITCC |
Keywords | DocType | ISBN |
ontology-based classification,training setof emails,anunderlying bayesian classifier,forthese feature,foremail classification,associated probability,feature vector,knowledge representation,classification,ontology,bayesian classifier,feature vectors | Conference | 0-7695-1916-4 |
Citations | PageRank | References |
14 | 0.91 | 2 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazem Taghva | 1 | 350 | 43.51 |
| Julie Borsack | 2 | 208 | 22.53 |
| jeffrey coombs | 3 | 89 | 7.73 |
| Allen Condit | 4 | 210 | 22.95 |
| Steve Lumos | 5 | 14 | 0.91 |
| thomas a nartker | 6 | 14 | 0.91 |