We introduce a technique based on data mining algorithms for classifying incoming messages, as a basis for an overall architecture for maintenance and management of e-mail messages. We exploit clustering techniques for grouping structured and unstructured information extracted from e-mail messages in an unsupervised way, and exploit the resulting algorithm in the process of folder creation (and maintenance) and e-mail redirection. Some initial experimental results show the effectiveness of the technique, both from an efficiency and a quality-of-results viewpoint.

A Framework for Adaptive Mail Classification

Giuseppe Manco;Elio Masciari;
2002

Abstract

We introduce a technique based on data mining algorithms for classifying incoming messages, as a basis for an overall architecture for maintenance and management of e-mail messages. We exploit clustering techniques for grouping structured and unstructured information extracted from e-mail messages in an unsupervised way, and exploit the resulting algorithm in the process of folder creation (and maintenance) and e-mail redirection. Some initial experimental results show the effectiveness of the technique, both from an efficiency and a quality-of-results viewpoint.
2002
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Inglese
14th International Conference on Tools with Artificial Intelligence
387
394
0-7695-1849-4
Sì, ma tipo non specificato
4 June 2002 through 6 November 2002
Washington, DC; United States
3
none
Manco, Giuseppe; Masciari, Elio; Tagarell, Andrea
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/236496
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