A great amount of machine learning techniques have been applied to problems where data is collected over an extended period of time. However, the disadvantage with many real-world applications is that the distribution underlying the data is likely to change over time. In these situations, a problem that many global eager learners face is their inability to adapt to local concept drift. Concept ...

A study of the impact spam messages and modern threats on process e-mail exchange in corporate information system was conducted. The role its influence systems has been studied. Peculiarities countermeasures technologies for protection against have On basis research carried out work, a Bayesian classifier developed filtering e-mails postal system.

Recently, the Internet has been a basis of our cultural life. Web provides a virtual huge space of information, where an emotional experience, a political idea, a cultural custom, and the advice of manners of music, the business, the arts, photographs, and literatures, etc. are digitalized at a low price and are shared for our current culture. One of major other tools gives E-mail communication...

In this paper, we propose methods and heuristics having high accuracies and low time complexities for filtering spam e-mails. The methods are based on the n-gram approach and a heuristics which is referred to as the first n-words heuristics is devised. Though the main concern of the research is studying the applicability of these methods on Turkish e-mails, they were also applied to English e-m...

In this paper we present Linger a neural network based system for automated e-mail classification. Two scenarios are explored: filing e-mails into folders and spam e-mail filtering. Extensive experiments indicate that Linger compares favourably to other classification techniques. We study the effects of various feature selection, weighting and normalization methods, and also the portability of ...

We present a simple, yet highly accurate, spam ltering program, called Spam-Cop, which is able to identify about 92% of the spams while misclassifying only about 1.16% of the nonspam e-mails. SpamCop treats an e-mail message as a multiset of words and employs a naive Bayes algorithm to determine whether or not a message is likely to be a spam. Compared with keyword-spotting rules, the probabili...

In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a supervised learning setting, we investigate the use of random forest for automatic e-mail filing into folders and spam e-mail filtering. We show that random forest is a good choice for these tasks as it runs fast on large an...

pam is a serious universal problem which causes problems for almost all computer users. This issue affects not only normal users of the internet, but also causes a big problem for companies and organizations since it costs a huge amount of money in lost productivity, wasting users’ time and network bandwidth. Many studies on spam indicate that spam cost organizations billions of dollars yearly....