Externally growing self-organizing maps and its application to e-mail database visualization and exploration

被引：11

作者：

Nuernberger, Andreas

Detyniecki, Marcin

机构：

[1] Univ Magdeburg, FIN IWS IR Grp, D-39106 Magdeburg, Germany

[2] Univ Paris 06, CNRS, Lab Informat, F-75015 Paris, France

来源：

APPLIED SOFT COMPUTING | 2006年 / 6卷 / 04期

关键词：

growing self-organizing maps; e-mail; document classification; visualization; information retrieval;

D O I：

10.1016/j.asoc.2005.11.008

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we present an approach to organize and classify e-mails using self-organizing maps. The aim is on the one hand to provide an intuitive visual profile of the considered mailing lists and on the other hand to offer an intuitive navigation tool, were similar e-mails are located close to each other, so that the user can scan easily for e-mails similar in content. To be able to evaluate this approach we have developed a prototypical software tool that imports messages from a mailing list and arranges/ groups these e-mails based on a similarity measure. The tool combines conventional keyword search methods with a visualization of the considered e-mail collection. The prototype was developed based on externally growing self-organizing maps, which solve some problems of conventional self-organizing maps and which are computationally viable. Besides the underlying algorithms we present and discuss some system evaluations in order to show the capabilities of the approach. (C) 2005 Elsevier B.V. All rights reserved.

引用

页码：357 / 371

页数：15

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