Name
Abstract | ||
|---|---|---|
In order to cope with the problem of spam soaring, a personalized e-mail filtering method based on UCON is proposed. E-mails from different senders were classified as junk e-mail, suspicious e-mail and normal e-mail by trust third-party according to the maintained blacklist and embedded machine learning technology online. Suspicious e-mails will be classified further from users' point of view manually. Then the incoming e-mails would be sifted and processed differently according to their classification. Experiments results illustrate the method of the paper not only provide a personalization filtering but also more accurate and effective than the popular statistical spam filtering system. © 2013 ACADEMY PUBLISHER. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.4304/jsw.8.4.860-867 | JSW |
Keywords | Field | DocType |
personalization filtering,spam filtering,usage control | World Wide Web,Computer science,Blacklist,Filter (signal processing),Personalization | Journal |
Volume | Issue | Citations |
8 | 4 | 0 |
PageRank | References | Authors |
0.34 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chang-da Wang | 1 | 6 | 2.29 |
| Tingting Gong | 2 | 0 | 0.68 |
| Patricia Ghann | 3 | 0 | 0.68 |