Hierarchical Clustering of Document Archives with the Growing Hierarchical Self-Organizing Map

Authors:
Michael Dittenbach;Dieter Merkl;Andreas Rauber
Affiliations:
-;-;-
Venue:
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Year:
2001

Citing 3
Cited 0

Self-organizing maps

Self-organizing maps
The Growing Hierarchical Self-Organizing Map

IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Dynamic self-organizing maps with controlled growth for knowledge discovery

IEEE Transactions on Neural Networks

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Abstract

With the increasing amount of information available in electronic document collections, methods for organizing these collections to allowtopic-orien ted browsing and orientation gain increasing importance. In this paper, we present the Growing Hierarchical Self-Organizing Map, which allows an automatic hierarchical decomposition and organization of documents. We present a case study based on a 3-month article collection from an Austrian daily newspaper.