Name
Title | ||
|---|---|---|
Semi-Synthetic Data for Enhanced SMS Spam Detection: [Using Synthetic Minority Oversampling TEchnique SMOTE] |
Abstract | ||
|---|---|---|
In this paper, we study the effect of using Synthetic Minority Oversampling TEchnique on the detection of SMS spam. The study shows an improved spam detection performance of the classifiers trained on semi-synthetic datasets compared to the performance of the same classifiers trained on the original dataset. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2668260.2668307 | MEDES |
Keywords | Field | DocType |
database applications,sms spam,experimentation,security,synthetic minority oversampling technique,classification,natural language processing,performance | Data mining,Oversampling,Computer science,Synthetic data,Sms spam | Conference |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ala Eshmawi | 1 | 0 | 0.68 |
| Suku Nair | 2 | 140 | 12.00 |