In this research we propose a model for automatic domain-relevant term extraction from Arabic text corpus. The proposed model uses a hybrid approach composed of linguistic and statistical methods to extract terms relevant to specific domains depending on prevalence and tendency term ranking mechanism. This increases precision and recall as a measures of relevancy of extracted terms to a specific domain.
LightAttachment is a Postfix content filter designed to extract large attachment files from mails, saved them to a data server and replace them by a link into the mails. Its activity is monitored by a complete statistical reporting system.
SPAM-Buster is a Java application for filtering SPAM based on statistical algorithms (currently Bayesian). The platform independant application can be used as graphical end-user client and additional service for mail server.
Java based mailing list software with features for both statistical and rule based filtering of messages. The purpose is to create an easily extendable system that can be modified to suit the specific needs of the list provider.