Abstract
Detecting alert e-mails received daily by millions of subscribers from online news providers is a relatively new area of research which falls within the e-mail filtering field of research. Alert e-mails may address government, political issues, breaking news, and criminal attacks. This article proposes a hybrid approach based on both the Graham statistical filter and rule-based filters to detect and filter Arabic alert e-mails. The approach is basically language-independent. To test the performance of the proposed approach, several experiments have been conducted using a set of 1500 Arabic messages related to criminal activities collected manually from some news websites such as Al-Jazeera Net and BBC Arabic news. The results showed that the proposed approach has achieved a competitive performance in terms of accuracy, precision, and F-measure, where about 87% of the messages tested have been correctly detected and filtered by the proposed filter.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 87-99 |
| Number of pages | 13 |
| Journal | Journal of Information Science |
| Volume | 38 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2012 |
| Externally published | Yes |
Keywords
- Arabic language processing
- Graham statistical filter
- alert e-mail
- data classification
- rule-based filters
ASJC Scopus subject areas
- Information Systems
- Library and Information Sciences
