Journal of Intelligent Information Systems

, Volume 30, Issue 2, pp 153–181

Mining categories for emails via clustering and pattern discovery


DOI: 10.1007/s10844-006-0024-x

Cite this article as:
Manco, G., Masciari, E. & Tagarelli, A. J Intell Inf Syst (2008) 30: 153. doi:10.1007/s10844-006-0024-x


The continuous exchange of information by means of the popular email service has raised the problem of managing the huge amounts of messages received from users in an effective and efficient way. We deal with the problem of email classification by conceiving suitable strategies for: (1) organizing messages into homogeneous groups, (2) redirecting further incoming messages according to an initial organization, and (3) building reliable descriptions of the message groups discovered. We propose a unified framework for handling and classifying email messages. In our framework, messages sharing similar features are clustered in a folder organization. Clustering and pattern discovery techniques for mining structured and unstructured information from email messages are the basis of an overall process of folder creation/maintenance and email redirection. Pattern discovery is also exploited for generating suitable cluster descriptions that play a leading role in cluster updating. Experimental evaluation performed on several personal mailboxes shows the effectiveness of our approach.


Email classification Text mining Clustering Pattern discovery 


H.2.8 (Database Management)

Database Applications–Data Mining

I.5.3 (Pattern Recognition)

Clustering–Algorithms, Similarity measures

I.5.4 (Pattern Recognition)

Applications–Text processing

H.4.3 (Information Systems Applications)

Communications Applications–electronic mail

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Giuseppe Manco
    • 1
  • Elio Masciari
    • 1
  • Andrea Tagarelli
    • 2
  1. 1.ICAR-CNRRende (CS)Italy
  2. 2.DEISUniversity of CalabriaRende (CS)Italy

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