Abstract. An approach to intelligent email categorization has been proposed using fast machine learning algorithms. The categorization is based on not only the body but also the header of an email message. The metadata (e.g. sender name, organization, etc.) provide additional information that can be exploited and improve the categorization capability. Results of experiments on real email data demonstrate the feasibility of our approach. In particular, it is shown that categorization based only on the header information is comparable or superior to that based on all the information in a message
Office workers everywhere are drowning in email---not only spam, but also large quantities of legiti...
Real-time classification of massive email data is a challenging task that presents its own particula...
This diploma's thesis is based around creating a classifier, which will be able to recognize an emai...
Classifying emails into distinct labels can have a great impact on customer support. By using machin...
This paper puts forward a hierarchical approach for categorizing emails with the ME model based on i...
This paper presents the design and implementation of a system to group and summarize email messages....
The goal of this project is to construct a machine learning algorithmthat improves over time. This w...
The growing problem of unsolicited bulk email and the growth of the volume of email received has gen...
The increasing volume of unsolicited mass e-mail (otherwise called spam) has generated a need for re...
Classifying e-mails into distinct labels can have a great impact on customer support. By using machi...
In this thesis I evaluate different ways of classifying email messages in the absence of a large num...
The goal of email classification is to classify user emails into spam and legitimate ones. Many supe...
Focusing on the uncertainty of classifying emails based-on email content and the incompleteness of e...
AbstractInformation users depend heavily on emails’ system as one of the major sources of communicat...
Abstract. Real-time classification of massive email data is a chal-lenging task that presents its ow...
Office workers everywhere are drowning in email---not only spam, but also large quantities of legiti...
Real-time classification of massive email data is a challenging task that presents its own particula...
This diploma's thesis is based around creating a classifier, which will be able to recognize an emai...
Classifying emails into distinct labels can have a great impact on customer support. By using machin...
This paper puts forward a hierarchical approach for categorizing emails with the ME model based on i...
This paper presents the design and implementation of a system to group and summarize email messages....
The goal of this project is to construct a machine learning algorithmthat improves over time. This w...
The growing problem of unsolicited bulk email and the growth of the volume of email received has gen...
The increasing volume of unsolicited mass e-mail (otherwise called spam) has generated a need for re...
Classifying e-mails into distinct labels can have a great impact on customer support. By using machi...
In this thesis I evaluate different ways of classifying email messages in the absence of a large num...
The goal of email classification is to classify user emails into spam and legitimate ones. Many supe...
Focusing on the uncertainty of classifying emails based-on email content and the incompleteness of e...
AbstractInformation users depend heavily on emails’ system as one of the major sources of communicat...
Abstract. Real-time classification of massive email data is a chal-lenging task that presents its ow...
Office workers everywhere are drowning in email---not only spam, but also large quantities of legiti...
Real-time classification of massive email data is a challenging task that presents its own particula...
This diploma's thesis is based around creating a classifier, which will be able to recognize an emai...