Self-organising map techniques for graph data applications to clustering of XML documents

Authors:
A. C. Tsoi;M. Hagenbuchner;A. Sperduti
Affiliations:
Monash e-Research Centre, Monash University, Victoria, Australia;Faculty of Informatics, University of Wollongong, Wollongong, NSW, Australia;Dipartimento di Matematica Pura ed Applicata, University of Padova, Padova, Italy
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

Citing 3
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Self-Organizing Maps

Self-Organizing Maps
Information Theory, Inference & Learning Algorithms

Information Theory, Inference & Learning Algorithms
A self-organizing map for adaptive processing of structured data

IEEE Transactions on Neural Networks

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Abstract

In this paper, neural network techniques based on Kohonen’s self-organising map method which can be trained in an unsupervised fashion and applicable to the processing of graph structured inputs are described. Then it is shown how such techniques can be applied to the problems of clustering of XML documents.