This paper introduces a new concept to the processing of graph struc- tured information using self organising map framework. Previous approaches to this problem were limited to the processing of bounded graphs. The computational complexity of such methods grows rapidly with the level of connectivity, and are restricted to the processing of positional graphs. The concept proposed in this paper addresses these issues by reducing the computational demand, and by allowing the processing of non-positional graphs. This is achieved by utilising the state space of the self organising map instead of the states of the nodes in the graph for processing.

Self-Organizing Maps for cyclic and unbound graphs

SPERDUTI, ALESSANDRO;
2008

Abstract

This paper introduces a new concept to the processing of graph struc- tured information using self organising map framework. Previous approaches to this problem were limited to the processing of bounded graphs. The computational complexity of such methods grows rapidly with the level of connectivity, and are restricted to the processing of positional graphs. The concept proposed in this paper addresses these issues by reducing the computational demand, and by allowing the processing of non-positional graphs. This is achieved by utilising the state space of the self organising map instead of the states of the nodes in the graph for processing.
2008
ESANN'2008 proceedings, European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, Bruges (Belgium), 23-25 April 2008
2930307080
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2274021
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