A hybrid approach to detecting alerts in Arabic e-mail messages

Qasem A. Al-Radaideh, Ahmed F. Aleroud, Emad M. Al-Shawakfa

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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 languageEnglish (US)
Pages (from-to)87-99
Number of pages13
JournalJournal of Information Science
Volume38
Issue number1
DOIs
StatePublished - Feb 2012
Externally publishedYes

Keywords

  • alert e-mail
  • Arabic language processing
  • data classification
  • Graham statistical filter
  • rule-based filters

ASJC Scopus subject areas

  • Information Systems
  • Library and Information Sciences

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