| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 534193 | Pattern Recognition Letters | 2012 | 6 Pages |
Abstract
⺠Propose an mobile spam classification using a variety of new, stylistically motivated features. ⺠Stylistic features improve the performance of mobile spam classifiers. ⺠Stylistic features is both effective in English and Korean SMS datasets.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Dae-Neung Sohn, Jung-Tae Lee, Kyoung-Soo Han, Hae-Chang Rim,