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Information users depend heavily on emails’ system as one of the major sources of communication. Its importance and usage are continuously growing despite the evolution of mobile applications, social networks, etc. Emails are used on both the personal and professional levels. They can be considered as official documents in communication among users. Emails’ data mining and analysis can be conducted for several purposes such as: Spam detection and classification, subject classification, etc. In this paper, a large set of personal emails is used for the purpose of folder and subject classifications. Algorithms are developed to perform clustering and classification for this large text collection. Classification based on NGram is shown to be the best for such large text collection especially as text is Bi-language (i.e. with English and Arabic content).

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This document was originally published in Journal of King Saud University - Computer and Information Sciences by Elsevier. This work is provided under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license. Details regarding the use of this work can be found at: doi: 10.1016/j.jksuci.2014.03.014