Title :
Unsupervised email vector space model (UEVSM)
Author_Institution :
Dept. of Electron. & Comput. Eng., Univ. of Portsmouth, Portsmouth, UK
Abstract :
There are many challenges of grouping email messages. One of the challenging issues of email message group is to pinpoint when the clustering process accumulates accurate and sufficient information for grouping is archived. In this work, an unsupervised machine learning technique has been developed based on unsupervised clustering method (UCM). The proposed unsupervised clustering method is new and different from other existing UCMs such as: email evolving clustering method.
Keywords :
electronic mail; pattern clustering; unsupervised learning; vectors; email message group; unsupervised clustering method; unsupervised email vector space model; unsupervised machine learning technique; Europe; Indexes; Semantics;
Conference_Titel :
Internet Technology and Secured Transactions (ICITST), 2010 International Conference for
Conference_Location :
London
Print_ISBN :
978-1-4244-8862-9
Electronic_ISBN :
978-0-9564263-6-9