By feeding personal e-mails into the training set, personalized content-based spam filters are believed to classify e-mails in higher accuracy. However, filters trained by both sp...
The volume of spam e-mails has grown rapidly in the last two years resulting in increasing costs to users, network operators, and e-mail service providers (ESPs). E-mail users dem...
Typically, spam filters are built on the assumption that the characteristics of e-mails in the training set is identical to those in individual users’ inboxes on which it will b...
The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous fault-prone detection approaches are based on software metrics...
Many of the first successful applications of statistical learning to anti-spam filtering were personalized classifiers that were trained on an individual user’s spam and ham ...